{ "section": "papers", "kind": "paper", "canonical": "https://evemisslab.com/ai/papers/", "count": 24, "records": [ { "id": "PAP-2026-0009", "kind": "paper", "label": "Paper 09 — Probability is not Bayesian", "created_at": "2026-09-10", "updated_at": "2026-09-10", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0009/", "eml_provenance": { "source": "EveMissLab research collection: Adaptive Epistemic Systems (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each lab's own result reports", "extracted_at": "2026-09-11", "generator": "tools/extract_aes/extract.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "A layered vocabulary from stochastic to generalized Bayesian and a Bayesian authenticity test for updates that are only redescribed as Bayesian.", "eml_summary_zh": "從 stochastic 到 generalized Bayesian 的分層詞彙，以及檢查「事後被說成 Bayesian」的 Bayesian authenticity test。", "eml_label_zh": "概率不等於貝葉斯——從隨機系統、概率模型到 Bayesian 更新的認識論邊界", "eml_primary_domain": "Formal AI", "eml_program_id": "PRG-2026-0001", "eml_publication_type": "series paper (Adaptive Epistemic Systems Series, 11 papers)", "eml_data_basis": "THEORY", "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_date": "2026-09-10", "eml_source_artifact": "Adaptive_Epistemic_Systems_Series_Paper_09_Probability_Is_Not_Bayesian_v0.1.md", "eml_checksums": { "sha256": "3565602d4854c98d76ced7e46f250164f2ae4c7d51b868de5dd12fecc137425f" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 9/11" ], "eml_ai_collaborators": [ "Sol (GPT-5.6, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0009/", "json": "/ai/papers/PAP-2026-0009/index.json" }, { "id": "PAP-2026-0005", "kind": "paper", "label": "Paper 05 — Memory, algorithm libraries and reusable solution paths", "created_at": "2026-09-08", "updated_at": "2026-09-08", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0005/", "eml_provenance": { "source": "EveMissLab research collection: Adaptive Epistemic Systems (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each lab's own result reports", "extracted_at": "2026-09-11", "generator": "tools/extract_aes/extract.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Algorithms, tools, contracts, costs and outcome history become capability nodes; Reuse ≻ Adapt ≻ Create.", "eml_summary_zh": "算法、工具、契約、成本與成敗歷史成為能力節點；Reuse ≻ Adapt ≻ Create。", "eml_label_zh": "記憶、算法庫與可重用問題求解路徑——從世界模型到能力模型的累積式智能架構", "eml_primary_domain": "Computation", "eml_program_id": "PRG-2026-0001", "eml_publication_type": "series paper (Adaptive Epistemic Systems Series, 11 papers)", "eml_data_basis": "THEORY", "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_date": "2026-09-08", "eml_source_artifact": "Adaptive_Epistemic_Systems_Series_Paper_05_Memory_Algorithms_and_Reusable_Solution_Paths_v0.1.md", "eml_checksums": { "sha256": "e54a04fb440fef6a2835017bf92338d1f85b7e3188252c2bd5b2ed213b8d52cd" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 5/11" ], "eml_ai_collaborators": [ "Sol (GPT-5.6, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0005/", "json": "/ai/papers/PAP-2026-0005/index.json" }, { "id": "PAP-2026-0006", "kind": "paper", "label": "Paper 06 — Substrate-neutral computational containers", "created_at": "2026-09-08", "updated_at": "2026-09-08", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0006/", "eml_provenance": { "source": "EveMissLab research collection: Adaptive Epistemic Systems (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each lab's own result reports", "extracted_at": "2026-09-11", "generator": "tools/extract_aes/extract.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Any execution environment with representable input, valid transition and readable output is a compute container; algorithms and containers are scheduled jointly.", "eml_summary_zh": "任何具可表示輸入、有效轉換與可讀輸出的執行環境都是計算容器；算法與容器聯合調度。", "eml_label_zh": "載體中立的計算容器理論——從算法選擇到異質計算載體聯合調度", "eml_primary_domain": "Computation", "eml_program_id": "PRG-2026-0001", "eml_publication_type": "series paper (Adaptive Epistemic Systems Series, 11 papers)", "eml_data_basis": "THEORY", "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_date": "2026-09-08", "eml_source_artifact": "Adaptive_Epistemic_Systems_Series_Paper_06_Substrate_Neutral_Computational_Containers_v0.1.md", "eml_checksums": { "sha256": "dca4838b1274db5f51668e3dde0babdaaf27fd7e6f1ce9d2a2a82c1b978b3d33" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 6/11" ], "eml_ai_collaborators": [ "Sol (GPT-5.6, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0006/", "json": "/ai/papers/PAP-2026-0006/index.json" }, { "id": "PAP-2026-0007", "kind": "paper", "label": "Paper 07 — Blind-derived AI: do different first principles converge on one engineering form?", "created_at": "2026-09-08", "updated_at": "2026-09-08", "values": { "eml_status": "STABLE", "eml_evidence_level": "E1", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0007/", "eml_provenance": { "source": "EveMissLab research collection: Adaptive Epistemic Systems (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each lab's own result reports", "extracted_at": "2026-09-11", "generator": "tools/extract_aes/extract.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Treats the first six papers as a blind-derivation experiment and proposes a protocol and five levels of similarity for comparing the result with modern AI.", "eml_summary_zh": "把前六篇視為一次盲推導實驗，提出比較協定與五種相似性層級，用來對照現代 AI。", "eml_label_zh": "盲推導 AI——不同第一原理是否收斂到同一工程形態？", "eml_primary_domain": "AI Architecture", "eml_program_id": "PRG-2026-0001", "eml_publication_type": "series paper (Adaptive Epistemic Systems Series, 11 papers)", "eml_data_basis": "THEORY", "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_date": "2026-09-08", "eml_source_artifact": "Adaptive_Epistemic_Systems_Series_Paper_07_Blind_Derivation_and_AI_Architecture_Convergence_v0.1.md", "eml_checksums": { "sha256": "2a0626405e60d8e57ec1b960272f06283caa32d53f33837e634a026360b7c172" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 7/11" ], "eml_ai_collaborators": [ "Sol (GPT-5.6, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0007/", "json": "/ai/papers/PAP-2026-0007/index.json" }, { "id": "PAP-2026-0008", "kind": "paper", "label": "Paper 08 — Intelligent architecture attractors: at which level does difference live?", "created_at": "2026-09-08", "updated_at": "2026-09-08", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0008/", "eml_provenance": { "source": "EveMissLab research collection: Adaptive Epistemic Systems (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each lab's own result reports", "extracted_at": "2026-09-11", "generator": "tools/extract_aes/extract.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Six levels of architectural difference, architecture equivalence classes and attractor basins; the executed architecture is the architecture.", "eml_summary_zh": "六個架構差異層級、架構等價類與吸引域；被執行的架構才是架構。", "eml_label_zh": "智能架構吸引子——差異究竟存在於哪一層？", "eml_primary_domain": "AI Architecture", "eml_program_id": "PRG-2026-0001", "eml_publication_type": "series paper (Adaptive Epistemic Systems Series, 11 papers)", "eml_data_basis": "THEORY", "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_date": "2026-09-08", "eml_source_artifact": "Adaptive_Epistemic_Systems_Series_Paper_08_Intelligent_Architecture_Attractors_v0.1.md", "eml_checksums": { "sha256": "779cec6ab5f3bf7f99e8fe2d118adeba88d565e43b5898459b190f4054b3a76e" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 8/11" ], "eml_ai_collaborators": [ "Sol (GPT-5.6, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0008/", "json": "/ai/papers/PAP-2026-0008/index.json" }, { "id": "PAP-2026-0010", "kind": "paper", "label": "Paper 10 — Bayes within Bayes: who authorizes the update rule?", "created_at": "2026-09-08", "updated_at": "2026-09-08", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0010/", "eml_provenance": { "source": "EveMissLab research collection: Adaptive Epistemic Systems (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each lab's own result reports", "extracted_at": "2026-09-11", "generator": "tools/extract_aes/extract.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Prior, likelihood and hypothesis space need an authorization Bayes' rule cannot give; meta-epistemic configuration becomes part of the architecture.", "eml_summary_zh": "Prior、likelihood 與假設空間需要一個 Bayes 公式給不出的授權；meta-epistemic configuration 成為架構的一部分。", "eml_label_zh": "貝葉斯中的貝葉斯——誰授權更新規則？從 Prior、Likelihood 到 Meta-Epistemology 的遞歸問題", "eml_primary_domain": "Formal AI", "eml_program_id": "PRG-2026-0001", "eml_publication_type": "series paper (Adaptive Epistemic Systems Series, 11 papers)", "eml_data_basis": "THEORY", "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_date": "2026-09-08", "eml_source_artifact": "Adaptive_Epistemic_Systems_Series_Paper_10_Bayes_Within_Bayes_Meta_Epistemic_Justification_v0.1.md", "eml_checksums": { "sha256": "b1d66639204c40e843791aa06f87b7d5a796d9476ffa2adc25f80cf954dd987c" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 10/11" ], "eml_ai_collaborators": [ "Sol (GPT-5.6, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0010/", "json": "/ai/papers/PAP-2026-0010/index.json" }, { "id": "PAP-2026-0011", "kind": "paper", "label": "Paper 11 — If it is really stronger, I was wrong; if not, what did we find? The final experimental verdict", "created_at": "2026-09-08", "updated_at": "2026-09-08", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0011/", "eml_provenance": { "source": "EveMissLab research collection: Adaptive Epistemic Systems (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each lab's own result reports", "extracted_at": "2026-09-11", "generator": "tools/extract_aes/extract.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Fixes the verdict map before the runtime exists — Distinct Advantage, Operational Convergence, Behavioral Equivalence Only, Inconclusive, Architecture Worse — with fidelity gates, ablation, equivalence testing and the rule that if every outcome confirms, nothing was explained.", "eml_summary_zh": "在 runtime 存在之前就固定判決表——Distinct Advantage、Operational Convergence、Behavioral Equivalence Only、Inconclusive、Architecture Worse——附 fidelity gate、消融、等價檢驗，以及「若每種結果都算確認，就什麼都沒解釋」的規則。", "eml_label_zh": "如果它真的更強，我錯了；如果沒有，我們又發現了什麼？——自適應認識系統的最終實驗判決與可證偽收束", "eml_primary_domain": "AI Architecture", "eml_program_id": "PRG-2026-0001", "eml_publication_type": "series paper (Adaptive Epistemic Systems Series, 11 papers)", "eml_data_basis": "THEORY", "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_date": "2026-09-08", "eml_source_artifact": "Adaptive_Epistemic_Systems_Series_Paper_11_Final_Experimental_Verdict_v0.1.md", "eml_checksums": { "sha256": "fbd6ec4a0292ce78daa297ec2df3d209639875a7532ea77abcadaed294e4f012" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 11/11" ], "eml_ai_collaborators": [ "Sol (GPT-5.6, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0011/", "json": "/ai/papers/PAP-2026-0011/index.json" }, { "id": "PAP-2026-0012", "kind": "paper", "label": "The Probabilistic Appearance Convergence Conjecture (PACC)", "created_at": "2026-09-08", "updated_at": "2026-09-08", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0012/", "eml_provenance": { "source": "EveMissLab research collection: Adaptive Epistemic Systems (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each lab's own result reports", "extracted_at": "2026-09-11", "generator": "tools/extract_aes/extract.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Proposition paper: a system that does not take probability as a first-level primitive may, under finite information, competing candidates, resource limits, repeated update and forced choice, converge to forms that a probability model maps with low complexity. Distinguishes behavioural, representational, dynamical and attractor equivalence, and pre-registers the experiments' falsification conditions.", "eml_summary_zh": "命題論文：不以概率為第一級 primitive 的系統，在有限資訊、多候選競爭、資源約束、動態更新與必須選擇的條件下，可能收斂到概率模型能以低複雜度映射的形式。區分行為、表徵、動力學與吸引子四種等價，並預先登記實驗的否證條件。", "eml_label_zh": "概率表象收斂猜想——非概率式智能計算是否會在有限決策約束下收斂至概率型 AI？", "eml_primary_domain": "Model Representation", "eml_program_id": "PRG-2026-0001", "eml_publication_type": "proposition / conjecture paper", "eml_data_basis": "THEORY", "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_date": "2026-09-08", "eml_source_artifact": "PACC_Probability_Appearance_Convergence_Conjecture_v0.1_2026-09-08.md", "eml_tags": [ "zh-TW", "pre-experimental conjecture" ], "eml_ai_collaborators": [ "Sol (GPT-5.6, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0012/", "json": "/ai/papers/PAP-2026-0012/index.json" }, { "id": "PAP-2026-0013", "kind": "paper", "label": "Adaptive Epistemic AI Runtime — technical whitepaper v0.1", "created_at": "2026-09-08", "updated_at": "2026-09-08", "values": { "eml_status": "STABLE", "eml_evidence_level": "E1", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0013/", "eml_provenance": { "source": "EveMissLab research collection: Adaptive Epistemic Systems (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each lab's own result reports", "extracted_at": "2026-09-11", "generator": "tools/extract_aes/extract.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Compresses the eleven papers into a runtime architecture: AI = persistent world state + adaptive update + executable capability + verified action, with the minimal loop Input → Parse → Retrieve → Refresh → Plan → Select → Execute → Verify → Commit → Render. Ships JSON schemas for canonical nodes, capabilities and compute containers, a pseudocode skeleton and the AER-0 MVP roadmap.", "eml_summary_zh": "把十一篇壓縮成一套 runtime 架構：AI = 持久世界狀態 + 自適應更新 + 可執行能力 + 已驗證行動，最小迴圈為 Input → Parse → Retrieve → Refresh → Plan → Select → Execute → Verify → Commit → Render。附 canonical node、capability、compute container 的 JSON schema、pseudocode 骨架與 AER-0 MVP 路線圖。", "eml_label_zh": "Adaptive Epistemic AI Runtime——以非對稱時空張力、Canonical State、能力記憶與載體中立計算開發 AI 的技術白皮書", "eml_primary_domain": "AI Architecture", "eml_program_id": "PRG-2026-0001", "eml_publication_type": "technical whitepaper (implementation-oriented draft)", "eml_data_basis": "THEORY", "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_date": "2026-09-08", "eml_source_artifact": "Adaptive_Epistemic_AI_Runtime_v0.1_Technical_Whitepaper_Source_Package.zip", "eml_checksums": { "whitepaper.md sha256": "814cd2f35ce959c0d4e82bfc62189e3ed030f035326d64b15e46616aa47e03d3" }, "eml_tags": [ "zh-TW", "schemas", "roadmap" ], "eml_ai_collaborators": [ "Sol (GPT-5.6, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0013/", "json": "/ai/papers/PAP-2026-0013/index.json" }, { "id": "PAP-2026-0001", "kind": "paper", "label": "Paper 01 — Dynamic knowledge graphs under asymmetric spacetime tension", "created_at": "2026-09-07", "updated_at": "2026-09-07", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0001/", "eml_provenance": { "source": "EveMissLab research collection: Adaptive Epistemic Systems (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each lab's own result reports", "extracted_at": "2026-09-11", "generator": "tools/extract_aes/extract.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Lifts asymmetry from edge weight to effective time scale: nodes carry stability, decay, tension, impact and local valid time, so refresh is triggered locally instead of by one global clock.", "eml_summary_zh": "把非對稱性從邊權重提升到有效時間尺度：節點帶有穩定性、衰減、張力、影響度與局部有效時間，刷新由局部觸發而非單一全域時鐘。", "eml_label_zh": "非對稱時空張力下的動態知識圖——自適應世界狀態系統的第一原理框架", "eml_primary_domain": "AI Architecture", "eml_program_id": "PRG-2026-0001", "eml_publication_type": "series paper (Adaptive Epistemic Systems Series, 11 papers)", "eml_data_basis": "THEORY", "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_date": "2026-09-07", "eml_source_artifact": "Adaptive_Epistemic_Systems_Series_Paper_01_Asymmetric_Spacetime_Tension_v0.1.md", "eml_checksums": { "sha256": "5be05d99d3be868b53a89a459a8e3d9b9e9b6fc5d66c4faa049bb391bbda5fbd" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 1/11" ], "eml_ai_collaborators": [ "Sol (GPT-5.6, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0001/", "json": "/ai/papers/PAP-2026-0001/index.json" }, { "id": "PAP-2026-0002", "kind": "paper", "label": "Paper 02 — Stability is not a static value: freshness, decay and update tension", "created_at": "2026-09-07", "updated_at": "2026-09-07", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0002/", "eml_provenance": { "source": "EveMissLab research collection: Adaptive Epistemic Systems (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each lab's own result reports", "extracted_at": "2026-09-11", "generator": "tools/extract_aes/extract.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Freshness is decided by world change rate, source reliability, dependency structure, task risk and system impact — with risk-weighted tension, update debt, revalidation radius and event-triggered wake-up.", "eml_summary_zh": "新鮮度由世界變化速率、來源可靠性、依賴結構、任務風險與系統影響共同決定——含風險加權張力、更新債務、重驗證半徑與事件觸發喚醒。", "eml_label_zh": "穩定性不是靜態值——知識新鮮度、衰減率與更新張力的動態模型", "eml_primary_domain": "AI Architecture", "eml_program_id": "PRG-2026-0001", "eml_publication_type": "series paper (Adaptive Epistemic Systems Series, 11 papers)", "eml_data_basis": "THEORY", "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_date": "2026-09-07", "eml_source_artifact": "Adaptive_Epistemic_Systems_Series_Paper_02_Freshness_Decay_Update_Tension_v0.1.md", "eml_checksums": { "sha256": "7014b766ad178cbe19d1772f62dcd39c9e925b822913e552a8d494925389cf2f" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 2/11" ], "eml_ai_collaborators": [ "Sol (GPT-5.6, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0002/", "json": "/ai/papers/PAP-2026-0002/index.json" }, { "id": "PAP-2026-0003", "kind": "paper", "label": "Paper 03 — From dynamic graph to executable symbolic system: language as rendering, not canonical state", "created_at": "2026-09-07", "updated_at": "2026-09-07", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0003/", "eml_provenance": { "source": "EveMissLab research collection: Adaptive Epistemic Systems (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each lab's own result reports", "extracted_at": "2026-09-11", "generator": "tools/extract_aes/extract.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Four layers (world state, canonical symbols, executable operations, rendering); natural language is parsed into canonical state and rendered back out, never used as the state itself.", "eml_summary_zh": "四層結構（世界狀態、canonical 符號、可執行操作、rendering）；自然語言被解析進 canonical state 再 render 出來，永遠不直接當狀態本身。", "eml_label_zh": "從動態圖到可執行符號系統——自然語言作為世界狀態的 Rendering，而非 Canonical State", "eml_primary_domain": "AI Architecture", "eml_program_id": "PRG-2026-0001", "eml_publication_type": "series paper (Adaptive Epistemic Systems Series, 11 papers)", "eml_data_basis": "THEORY", "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_date": "2026-09-07", "eml_source_artifact": "Adaptive_Epistemic_Systems_Series_Paper_03_Executable_Symbolic_State_and_Rendering_v0.1.md", "eml_checksums": { "sha256": "1423707d3ca3e8074142103188633d25f9b94d409c27d5c2ea87a40153a34cf2" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 3/11" ], "eml_ai_collaborators": [ "Sol (GPT-5.6, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0003/", "json": "/ai/papers/PAP-2026-0003/index.json" }, { "id": "PAP-2026-0004", "kind": "paper", "label": "Paper 04 — World-knowledge expansion and the adaptive representation space", "created_at": "2026-09-07", "updated_at": "2026-09-07", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0004/", "eml_provenance": { "source": "EveMissLab research collection: Adaptive Epistemic Systems (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each lab's own result reports", "extracted_at": "2026-09-11", "generator": "tools/extract_aes/extract.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Effective structured information, not node count, measures capability growth; split/merge/delete/abstract/bridge keep the representation space adaptive.", "eml_summary_zh": "以有效結構化資訊而非節點數量衡量能力增長；split／merge／delete／abstract／bridge 讓表示空間持續可重構。", "eml_label_zh": "世界知識擴張與自適應表示空間——從節點數量增長到有效結構化資訊的能力擴張", "eml_primary_domain": "AI Architecture", "eml_program_id": "PRG-2026-0001", "eml_publication_type": "series paper (Adaptive Epistemic Systems Series, 11 papers)", "eml_data_basis": "THEORY", "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_date": "2026-09-07", "eml_source_artifact": "Adaptive_Epistemic_Systems_Series_Paper_04_Adaptive_Representation_Space_v0.1.md", "eml_checksums": { "sha256": "b31686e9acd0f52091ec46bbce801e1ccf9d28661f7b4cda6e1c86a8e946fe71" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 4/11" ], "eml_ai_collaborators": [ "Sol (GPT-5.6, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0004/", "json": "/ai/papers/PAP-2026-0004/index.json" }, { "id": "PAP-2026-0101", "kind": "paper", "label": "Paper 01 — What is a 'single turn', really? User turns, hidden loops, and the redefinition of single-pass intelligence", "created_at": "2026-09-02", "updated_at": "2026-09-02", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0101/", "eml_provenance": { "source": "EveMissLab research collection: Intelligence Physical Metrology (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each package's own reports", "extracted_at": "2026-09-11", "generator": "tools/extract_all.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Separates the chat-interface turn from model invocation, generation trajectory, agent loop and physical computation; defines externally loopless intelligence, a five-kind loop taxonomy and the single-pass condition U=1, G=1, R=1, L=0, S=0; introduces the event vector (Q, U, G, I, L, R, S, T, E, V_CST) and twelve invariants, starting with 'interaction compression ≠ computation compression'.", "eml_summary_zh": "把聊天介面的一輪從模型呼叫、生成軌跡、agent 迴圈與物理計算中分離；定義外部無迴圈智能、五類 LOOP 分類與 single-pass 條件 U=1、G=1、R=1、L=0、S=0；引入事件向量 (Q, U, G, I, L, R, S, T, E, V_CST) 與十二個不變式，第一條是「互動壓縮 ≠ 計算壓縮」。", "eml_label_zh": "一輪到底是一輪什麼？：使用者回合、隱藏 LOOP 與單次智能的重新定義", "eml_primary_domain": "Computation", "eml_program_id": "PRG-2026-0101", "eml_publication_type": "series paper (Intelligence Physical Metrology series, 10 papers); 公開純理論論文, 無 MVP", "eml_data_basis": "THEORY", "eml_date": "2026-09-02", "eml_doi_or_external_id": "EML-IPM-01", "eml_source_artifact": "IPM_01_一輪到底是一輪什麼_v0.1.zip!/IPM_01_一輪到底是一輪什麼_使用者回合隱藏LOOP與單次智能的重新定義_v0.1.md", "eml_checksums": { "paper .md sha256": "995cb61c0c35f14eeebf51a467e98c705a48e64f6d4fbd3d9880bff642220d2f" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 1/10", "role: 回合與執行邊界" ], "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_ai_collaborators": [ "Aletheia (GPT-5.6 Sol, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0101/", "json": "/ai/papers/PAP-2026-0101/index.json" }, { "id": "PAP-2026-0102", "kind": "paper", "label": "Paper 02 — What does intelligence compute once? A candidate theory of the minimum intelligent semantic execution unit", "created_at": "2026-09-02", "updated_at": "2026-09-02", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0102/", "eml_provenance": { "source": "EveMissLab research collection: Intelligence Physical Metrology (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each package's own reports", "extracted_at": "2026-09-11", "generator": "tools/extract_all.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Argues that token, FLOP, neuron activation, layer and 'thought' all fail as units of intelligent work and proposes μI, a resolution-relative semantic state transition with seven conditions, four candidate families, gross/effective counts, a semantic work vector and a cross-level map down to physical trace; explicitly a candidate ontology with no MVP.", "eml_summary_zh": "論證 token、FLOP、neuron activation、layer 與「想法」都不能當智能工作單位，提出 μI——相對於解析度的語意狀態轉換，帶七個條件、四個候選族、gross／effective 計數、語意工作向量與向下到物理軌跡的跨層映射；明言是候選本體、無 MVP。", "eml_label_zh": "智能到底算了一次什麼？：最小智能語意執行單位的候選理論", "eml_primary_domain": "Cognitive Science", "eml_program_id": "PRG-2026-0101", "eml_publication_type": "series paper (Intelligence Physical Metrology series, 10 papers); 公開純理論論文, 無 MVP", "eml_data_basis": "THEORY", "eml_date": "2026-09-02", "eml_doi_or_external_id": "EML-IPM-02", "eml_source_artifact": "IPM_02_智能到底算了一次什麼_v0.1.zip!/IPM_02_智能到底算了一次什麼_最小智能語意執行單位的候選理論_v0.1.md", "eml_checksums": { "paper .md sha256": "0183cf1066b211701efaec5e9f4c5dae5f25d3825b5940f870e33cb8a57ee201" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 2/10", "role: 語意工作中間層" ], "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_ai_collaborators": [ "Aletheia (GPT-5.6 Sol, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0102/", "json": "/ai/papers/PAP-2026-0102/index.json" }, { "id": "PAP-2026-0103", "kind": "paper", "label": "Paper 03 — From cognition to neurons: how human intelligence is measured across levels", "created_at": "2026-09-02", "updated_at": "2026-09-02", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0103/", "eml_provenance": { "source": "EveMissLab research collection: Intelligence Physical Metrology (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each package's own reports", "extracted_at": "2026-09-11", "generator": "tools/extract_all.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Reads cognitive science and neuroscience for method rather than numbers: Marr's levels extended to five, resource-rational operation costs, diffusion-model latent inference, encoding–decoding duality, population coding, causal perturbation, the 10 bits/s throughput lesson; yields cross-level triangulation and a D–A+ measurement grade for μI.", "eml_summary_zh": "向認知科學與神經科學借方法而非數字：Marr 三層擴成五層、resource-rational 的操作成本、擴散模型的潛變量推斷、編碼—解碼對偶、群體編碼、因果擾動、10 bits/s 的教訓；得出跨層三角化與 μI 的 D–A+ 測量等級。", "eml_label_zh": "從認知到神經元：人腦如何跨層測量智能計算", "eml_primary_domain": "Cognitive Science", "eml_program_id": "PRG-2026-0101", "eml_publication_type": "series paper (Intelligence Physical Metrology series, 10 papers); 公開純理論論文, 無 MVP", "eml_data_basis": "THEORY", "eml_date": "2026-09-02", "eml_doi_or_external_id": "EML-IPM-03", "eml_source_artifact": "IPM_03_從認知到神經元_v0.1.zip!/IPM_03_從認知到神經元_人腦如何跨層測量智能計算_v0.1.md", "eml_checksums": { "paper .md sha256": "3a1996da839c94367b1d6ffb69ce12309bc51b330b120aa181c514a0793daead" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 3/10", "role: 跨層測量與證據三角化" ], "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_ai_collaborators": [ "Aletheia (GPT-5.6 Sol, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0103/", "json": "/ai/papers/PAP-2026-0103/index.json" }, { "id": "PAP-2026-0104", "kind": "paper", "label": "Paper 04 — From neurons to joules: energy, thermodynamics, and physical lower bounds of intelligent computation", "created_at": "2026-09-02", "updated_at": "2026-09-02", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0104/", "eml_provenance": { "source": "EveMissLab research collection: Intelligence Physical Metrology (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each package's own reports", "extracted_at": "2026-09-11", "generator": "tools/extract_all.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Builds the energy account bottom-up the way neural energetics does (ion flux → ATP → joule), shows that a spike — and therefore a token or a μI — has no fixed energy, types energy as gross/baseline/marginal/attributed with a declared boundary, and keeps Landauer's kT ln 2 as a bound on erasure rather than the price of reasoning.", "eml_summary_zh": "照神經能量學的方式由下而上建能量帳（離子流 → ATP → 焦耳），說明一個 spike——因此一個 token 或一個 μI——沒有固定能量，把能量分型為 gross／baseline／marginal／attributed 並宣告邊界，Landauer 的 kT ln 2 只是抹除的下界而不是推理的價格。", "eml_label_zh": "從神經元到焦耳：智能計算的能量、熱力學與物理下界", "eml_primary_domain": "Computation", "eml_program_id": "PRG-2026-0101", "eml_publication_type": "series paper (Intelligence Physical Metrology series, 10 papers); 公開純理論論文, 無 MVP", "eml_data_basis": "THEORY", "eml_date": "2026-09-02", "eml_doi_or_external_id": "EML-IPM-04", "eml_source_artifact": "IPM_04_從神經元到焦耳_v0.1.zip!/IPM_04_從神經元到焦耳_智能計算的能量熱力學與物理下界_v0.1.md", "eml_checksums": { "paper .md sha256": "1d40befa4ae5bde20f694b7a6026dbca6a62d0d55514ebcd08629be8895a57e6" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 4/10", "role: 能源與熱力學" ], "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_ai_collaborators": [ "Aletheia (GPT-5.6 Sol, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0104/", "json": "/ai/papers/PAP-2026-0104/index.json" }, { "id": "PAP-2026-0105", "kind": "paper", "label": "Paper 05 — Computation is more than FLOPs: memory, interconnect, hardware occupancy, and computational spacetime volume", "created_at": "2026-09-02", "updated_at": "2026-09-02", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0105/", "eml_provenance": { "source": "EveMissLab research collection: Intelligence Physical Metrology (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each package's own reports", "extracted_at": "2026-09-11", "generator": "tools/extract_all.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Replaces FLOPs with a physical cost vector (typed ops, memory traffic by hierarchy, I/O, interconnect, residency, occupancy, time, energy), defines computational spacetime as a vector-first measure V_CST = ∫ R(t) dt with its own topology and peak footprint, and fixes CST measurement grades and boundaries; roofline and memory-wall results are the engineering backbone.", "eml_summary_zh": "以物理成本向量（分型運算、按層級的記憶體流量、I/O、互連、駐留、占用、時間、能量）取代 FLOPs，把計算時空定義為向量優先的測度 V_CST = ∫ R(t) dt，附拓撲與峰值占用，並固定 CST 測量等級與邊界；roofline 與 memory wall 是工程骨幹。", "eml_label_zh": "計算不是只有 FLOPs：記憶體、互連、硬體占用與計算時空體積", "eml_primary_domain": "Computation", "eml_program_id": "PRG-2026-0101", "eml_publication_type": "series paper (Intelligence Physical Metrology series, 10 papers); 公開純理論論文, 無 MVP", "eml_data_basis": "THEORY", "eml_date": "2026-09-02", "eml_doi_or_external_id": "EML-IPM-05", "eml_source_artifact": "IPM_05_計算不是只有FLOPs_v0.1.zip!/IPM_05_計算不是只有FLOPs_記憶體互連硬體占用與計算時空體積_v0.1.md", "eml_checksums": { "paper .md sha256": "588407fccc64b1bc1c6e501314543e17444729b0e6736bb9bb3d8174b25c99f8" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 5/10", "role: 完整物理成本與計算時空" ], "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_ai_collaborators": [ "Aletheia (GPT-5.6 Sol, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0105/", "json": "/ai/papers/PAP-2026-0105/index.json" }, { "id": "PAP-2026-0106", "kind": "paper", "label": "Paper 06 — How should output quality be measured? From formal correctness to structured intelligence quality", "created_at": "2026-09-02", "updated_at": "2026-09-02", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0106/", "eml_provenance": { "source": "EveMissLab research collection: Intelligence Physical Metrology (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each package's own reports", "extracted_at": "2026-09-11", "generator": "tools/extract_all.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Makes quality a relation Q(Y | task, spec, environment, boundary) measured as a structured vector in three layers (formal, structured, human residual) with hard gates, coverage split three ways, mutation-tested test strength, the specification–verification separation and a quality evidence ladder E–A+; efficiency is kept out of quality unless the specification puts it in.", "eml_summary_zh": "把品質變成關係 Q(Y | 任務、規格、環境、邊界)，以三層（形式化、結構化、人類殘餘）結構化向量量測，附 hard gate、三向覆蓋率、mutation 測出的測試強度、規格—驗證分離與 E–A+ 品質證據階梯；效率不進品質，除非規格把它放進去。", "eml_label_zh": "成果品質到底怎麼量？：從形式化正確性到結構化智能品質", "eml_primary_domain": "Evaluation", "eml_program_id": "PRG-2026-0101", "eml_publication_type": "series paper (Intelligence Physical Metrology series, 10 papers); 公開純理論論文, 無 MVP", "eml_data_basis": "THEORY", "eml_date": "2026-09-02", "eml_doi_or_external_id": "EML-IPM-06", "eml_source_artifact": "IPM_06_成果品質到底怎麼量_v0.1.zip!/IPM_06_成果品質到底怎麼量_從形式化正確性到結構化智能品質_v0.1.md", "eml_checksums": { "paper .md sha256": "25947f12ebfcff20aef144435dae50f9ffda1cccfdb143e319f8b2a6918356b8" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 6/10", "role: 客觀與結構化品質" ], "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_ai_collaborators": [ "Aletheia (GPT-5.6 Sol, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0106/", "json": "/ai/papers/PAP-2026-0106/index.json" }, { "id": "PAP-2026-0107", "kind": "paper", "label": "Paper 07 — Do not ask humans to numerically score their own feelings: IBQF binary measurement and low-burden quality evaluation", "created_at": "2026-09-02", "updated_at": "2026-09-02", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0107/", "eml_provenance": { "source": "EveMissLab research collection: Intelligence Physical Metrology (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each package's own reports", "extracted_at": "2026-09-11", "generator": "tools/extract_all.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Brings EveMissLab's IBQF/FDCS micro-binary idea into IPM as Binary Residual Quality Measurement: humans answer local yes/no or A/B items, Bradley–Terry / IRT-type models reconstruct a latent multidimensional quality, items are chosen adaptively by information gain per human cost, and rater disagreement is kept as structure; the low-burden advantage is stated as a testable hypothesis.", "eml_summary_zh": "把 EveMissLab 的 IBQF／FDCS 微觀二元想法帶進 IPM，成為二元殘餘品質測量：人只回答局部的是／否或 A／B，Bradley–Terry／IRT 類模型重建潛在多維品質，依每單位人類成本的資訊增益自適應選題，評審分歧當結構保留；低負擔優勢被寫成可檢驗的假說。", "eml_label_zh": "不要叫人類替自己的感覺打分數：IBQF 二元測量與低負擔品質評估", "eml_primary_domain": "Cognitive Science", "eml_program_id": "PRG-2026-0101", "eml_publication_type": "series paper (Intelligence Physical Metrology series, 10 papers); 公開純理論論文, 無 MVP", "eml_data_basis": "THEORY", "eml_date": "2026-09-02", "eml_doi_or_external_id": "EML-IPM-07", "eml_source_artifact": "IPM_07_不要叫人類替自己的感覺打分數_v0.1.zip!/IPM_07_不要叫人類替自己的感覺打分數_IBQF二元測量與低負擔品質評估_v0.1.md", "eml_checksums": { "paper .md sha256": "1267f620470cf0f900012dcfc58a9aa188116da77b2e0fb8f37470fd1122c5ee" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 7/10", "role: 人類殘餘品質與二元測量" ], "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_ai_collaborators": [ "Aletheia (GPT-5.6 Sol, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0107/", "json": "/ai/papers/PAP-2026-0107/index.json" }, { "id": "PAP-2026-0108", "kind": "paper", "label": "Paper 08 — How can natural language, images, and creative outputs be measured? A structured quality space for high-ambiguity artifacts", "created_at": "2026-09-02", "updated_at": "2026-09-02", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0108/", "eml_provenance": { "source": "EveMissLab research collection: Intelligence Physical Metrology (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each package's own reports", "extracted_at": "2026-09-11", "generator": "tools/extract_all.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Defines the typed quality space Q[domain, task, context, audience] = core ⊕ domain ⊕ task with construct graphs, the itemization pipeline construct → indicator → item → observation → latent estimate, a construct-validity gate, an open but versioned ontology, multimodal coupling dimensions and the rule that novelty is not creativity; every metric is one projection.", "eml_summary_zh": "定義有型別的品質空間 Q[領域、任務、情境、受眾] = core ⊕ domain ⊕ task，附構念圖、條目化管線 構念 → 指標 → 題目 → 觀測 → 潛在估計、構念效度閘、開放但有版本的本體、多模態耦合維度，以及「新穎不是創造力」的規則；每個指標都只是一個投影。", "eml_label_zh": "自然語言、圖像與創意如何被量？：高歧義成果的結構化品質空間", "eml_primary_domain": "Evaluation", "eml_program_id": "PRG-2026-0101", "eml_publication_type": "series paper (Intelligence Physical Metrology series, 10 papers); 公開純理論論文, 無 MVP", "eml_data_basis": "THEORY", "eml_date": "2026-09-02", "eml_doi_or_external_id": "EML-IPM-08", "eml_source_artifact": "IPM_08_自然語言圖像與創意如何被量_v0.1.zip!/IPM_08_自然語言圖像與創意如何被量_高歧義成果的結構化品質空間_v0.1.md", "eml_checksums": { "paper .md sha256": "d6bdb944f86c2274c880e651b551b6f1b3cd731d52affa588ecaf3089f7089a2" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 8/10", "role: 跨模態品質本體" ], "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_ai_collaborators": [ "Aletheia (GPT-5.6 Sol, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0108/", "json": "/ai/papers/PAP-2026-0108/index.json" }, { "id": "PAP-2026-0109", "kind": "paper", "label": "Paper 09 — How much intelligence remains without the loop? Single-pass capability, scaffolding dependence, and hidden computational cost", "created_at": "2026-09-02", "updated_at": "2026-09-02", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0109/", "eml_provenance": { "source": "EveMissLab research collection: Intelligence Physical Metrology (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each package's own reports", "extracted_at": "2026-09-11", "generator": "tools/extract_all.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Writes a system as (model, scaffolding vector), defines scaffolding gain, survival ratio SSR, dependence ratio SDR, scaffold cost multiplier SCM and marginal yields along the ablation ladder A0–A5, adds interaction graphs and Shapley-style attribution, hidden-retry and discarded-work accounting, a capability vector and S-grades; loop is not cheating, hiding its cost is.", "eml_summary_zh": "把系統寫成（模型，鷹架向量），定義鷹架增益、存活率 SSR、依賴率 SDR、鷹架成本倍率 SCM 與消融階梯 A0–A5 上的邊際產率，加上交互作用圖與 Shapley 式歸因、隱藏重試與丟棄工作的會計、能力向量與 S 等級；LOOP 不是作弊，藏成本才是。", "eml_label_zh": "拿掉 LOOP 還剩多少智能？：單次智能、鷹架依賴與隱藏計算成本", "eml_primary_domain": "Evaluation", "eml_program_id": "PRG-2026-0101", "eml_publication_type": "series paper (Intelligence Physical Metrology series, 10 papers); 公開純理論論文, 無 MVP", "eml_data_basis": "THEORY", "eml_date": "2026-09-02", "eml_doi_or_external_id": "EML-IPM-09", "eml_source_artifact": "IPM_09_拿掉LOOP還剩多少智能_v0.1.zip!/IPM_09_拿掉LOOP還剩多少智能_單次智能鷹架依賴與隱藏計算成本_v0.1.md", "eml_checksums": { "paper .md sha256": "a3e58b43f76a818508d6a52bffa931fc6c8767fe74aa27a9c714f9a5e84f599b" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 9/10", "role: 原生能力與鷹架依賴" ], "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_ai_collaborators": [ "Aletheia (GPT-5.6 Sol, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0109/", "json": "/ai/papers/PAP-2026-0109/index.json" }, { "id": "PAP-2026-0110", "kind": "paper", "label": "Paper 10 — How much physical world does an answer cost? A unified metrology framework for intelligence yield", "created_at": "2026-09-02", "updated_at": "2026-09-02", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0110/", "eml_provenance": { "source": "EveMissLab research collection: Intelligence Physical Metrology (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each package's own reports", "extracted_at": "2026-09-11", "generator": "tools/extract_all.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "Packs the four measurement objects into the canonical intelligence event, defines the intelligence yield vector and two-stage efficiency, sets Pareto comparison and the no-premature-scalarization principle, names four capability archetypes, fixes the IPM Minimum Reporting Standard v0.1 and restates the five falsifiable claims; IPM is a metrology candidate, not a discovered constant.", "eml_summary_zh": "把四個測量物件封裝成 canonical intelligence event，定義智能產率向量與兩段效率，訂下 Pareto 比較與不過早純量化原則，命名四種能力原型，固定 IPM 最低報告標準 v0.1 並重述五個可證偽命題；IPM 是計量學候選框架，不是被發現的常數。", "eml_label_zh": "一個答案值多少物理世界？：智能產率的統一計量框架", "eml_primary_domain": "Evaluation", "eml_program_id": "PRG-2026-0101", "eml_publication_type": "series paper (Intelligence Physical Metrology series, 10 papers); 公開純理論論文, 無 MVP", "eml_data_basis": "THEORY", "eml_date": "2026-09-02", "eml_doi_or_external_id": "EML-IPM-10", "eml_source_artifact": "IPM_10_一個答案值多少物理世界_v0.1.zip!/IPM_10_一個答案值多少物理世界_智能產率的統一計量框架_v0.1.md", "eml_checksums": { "paper .md sha256": "01564dac568d5783400897a41c70a520ffb6d615aa0d80d1b3a6ffffbeec2f2d" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "paper 10/10", "role: 統一封裝、Pareto 與 reporting standard" ], "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_ai_collaborators": [ "Aletheia (GPT-5.6 Sol, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0110/", "json": "/ai/papers/PAP-2026-0110/index.json" }, { "id": "PAP-2026-0111", "kind": "paper", "label": "IPM v0.1 canonical index — series overview, unified notation and the v0.2 experimental entry point", "created_at": "2026-09-02", "updated_at": "2026-09-02", "values": { "eml_status": "STABLE", "eml_evidence_level": "E0", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0111/", "eml_provenance": { "source": "EveMissLab research collection: Intelligence Physical Metrology (真本體論13)", "extracted_by": "Splice (Claude Code), reading the canonical UTF-8 sources and each package's own reports", "extracted_at": "2026-09-11", "generator": "tools/extract_all.py", "claim_boundary": "status, evidence level and result type follow the source artifact's own stated claim boundary; nothing is upgraded beyond what the report supports" }, "eml_summary": "The series' entry point: the canonical intelligence event, the dependency graph of the ten papers in three lines, a unified symbol table (turn/execution, semantic work, cross-level realization, energy, physical computation, computational spacetime and topology, quality, IBQF/BRQM, scaffolding, yield), the no-premature-scalarization principle, Pareto comparison, the 36-field minimum reporting standard, the ten-step comparison protocol, the series' core invariants, the five falsifiable propositions F1–F5, the v0.2 experiments A–E with the recommended order A → D → B → C → E, a minimal run schema and the versioning rule.", "eml_summary_zh": "系列入口：canonical intelligence event、十篇論文分三條線的依賴圖、統一符號表（回合／執行、語意工作、跨層實現、能量、物理計算、計算時空與拓撲、品質、IBQF／BRQM、鷹架、產率）、不過早純量化原則、Pareto 比較、36 欄最低報告標準、十步比較協定、系列核心不變式、五個可證偽命題 F1–F5、v0.2 實驗 A–E 與建議順序 A → D → B → C → E、最小 run schema 與版本規則。", "eml_label_zh": "IPM v0.1 Canonical Index：智能物理計量學系列總論、統一符號表與 v0.2 實驗入口", "eml_primary_domain": "Evaluation", "eml_program_id": "PRG-2026-0101", "eml_publication_type": "canonical series index (theory series entry point)", "eml_data_basis": "THEORY", "eml_date": "2026-09-02", "eml_doi_or_external_id": "EML-IPM v0.1 Canonical Index", "eml_source_artifact": "IPM_v0.1_Canonical_Series_Package.zip!/IPM_v0.1_Canonical_Index_統一符號表與v0.2實驗入口.md", "eml_checksums": { "index .md sha256": "54062e6af174ad899d801884d2e2ca682ad7306da4dd43397212e31ecb535b78" }, "eml_tags": [ "zh-TW", "canonical UTF-8 Markdown", "unified notation", "v0.2 experimental entry point" ], "eml_authors": [ "Neo.K (EveMissLab)" ], "eml_ai_collaborators": [ "Aletheia (GPT-5.6 Sol, OpenAI ChatGPT)" ] }, "canonical_url": "https://evemisslab.com/ai/papers/PAP-2026-0111/", "json": "/ai/papers/PAP-2026-0111/index.json" } ], "snapshot": { "snapshot_id": "AI-SNAPSHOT-v0.1-fe85b9694a45", "created_at": "2026-09-11T05:00:27Z", "format_version": "0.1", "sedb_baseline": "v0.4B contract; static source content/ai/", "generator_version": "evemisslab-com ai_research 0.1", "object_count": 124, "relation_count": 499, "artifact_count": 58 } }