{ "id": "RST-2026-0101", "kind": "result", "label": "Scaffolding response on three easy tasks: SSR = 1.0, 3.1× device energy at A5, 7.9–9.3× at A2–A4", "created_at": "2026-09-03", "updated_at": "2026-09-07", "values": { "eml_status": "STABLE", "eml_evidence_level": "E2", "eml_object_version": "0.1", "eml_canonical_url": "https://evemisslab.com/ai/results/RST-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": "Condition means (quality over available trials / wall s / device J): A0 0.5 / 10.21 / 1715.6; A1 0.5 / 9.87 / 1819.0; A2 0.5 / 79.09 / 15143.0; A3 0.6667 / 99.13 / 15921.5; A4 0.6667 / 69.08 / 13546.2; A5 0.5 / 31.91 / 5321.5. Energy ratio vs A0: A1 1.06, A2 8.827, A3 9.281, A4 7.896, A5 3.102. Total measured GPU energy 0.0891 kWh over 29.9 min of trial time; memory residency rises from 72.1 GiB·s (A0) to 714.6 GiB·s (A3).", "eml_summary_zh": "各條件平均（可用試驗的品質／wall 秒／裝置焦耳）：A0 0.5／10.21／1715.6；A1 0.5／9.87／1819.0；A2 0.5／79.09／15143.0；A3 0.6667／99.13／15921.5；A4 0.6667／69.08／13546.2；A5 0.5／31.91／5321.5。能量相對 A0：A1 1.06、A2 8.827、A3 9.281、A4 7.896、A5 3.102。36 次試驗共量得 GPU 能量 0.0891 kWh、試驗時間 29.9 分鐘；記憶體駐留從 A0 的 72.1 GiB·s 升到 A3 的 714.6 GiB·s。", "eml_label_zh": "三個簡單任務上的鷹架響應：SSR = 1.0，A5 的裝置能量 3.1×、A2–A4 7.9–9.3×", "eml_primary_domain": "Evaluation", "eml_program_id": "PRG-2026-0101", "eml_data_basis": "REAL MODEL", "eml_result_type": "MIXED", "eml_metrics": { "ssr": 1.0, "sdr": 0.0, "scm": { "device_energy_j": 3.1019, "wall_time_s": 3.1264 }, "by_condition": { "A0": { "quality_mean": 0.5, "quality_n": 4, "success_rate": 0.5, "wall_time_s": 10.21, "device_energy_j": 1715.6, "energy_ratio_vs_A0": 1.0, "gpu_peak_memory_gib": 7.23, "gpu_memory_residency_gib_s": 72.1, "gpu_utilization_integral_s": 6.57 }, "A1": { "quality_mean": 0.5, "quality_n": 4, "success_rate": 0.5, "wall_time_s": 9.87, "device_energy_j": 1819.0, "energy_ratio_vs_A0": 1.06, "gpu_peak_memory_gib": 7.32, "gpu_memory_residency_gib_s": 70.0, "gpu_utilization_integral_s": 6.26 }, "A2": { "quality_mean": 0.5, "quality_n": 4, "success_rate": 0.5, "wall_time_s": 79.09, "device_energy_j": 15143.0, "energy_ratio_vs_A0": 8.827, "gpu_peak_memory_gib": 7.28, "gpu_memory_residency_gib_s": 570.0, "gpu_utilization_integral_s": 54.09 }, "A3": { "quality_mean": 0.6667, "quality_n": 3, "success_rate": 0.6667, "wall_time_s": 99.13, "device_energy_j": 15921.5, "energy_ratio_vs_A0": 9.281, "gpu_peak_memory_gib": 7.34, "gpu_memory_residency_gib_s": 714.6, "gpu_utilization_integral_s": 70.02 }, "A4": { "quality_mean": 0.6667, "quality_n": 3, "success_rate": 0.6667, "wall_time_s": 69.08, "device_energy_j": 13546.2, "energy_ratio_vs_A0": 7.896, "gpu_peak_memory_gib": 7.28, "gpu_memory_residency_gib_s": 496.9, "gpu_utilization_integral_s": 46.93 }, "A5": { "quality_mean": 0.5, "quality_n": 4, "success_rate": 0.5, "wall_time_s": 31.91, "device_energy_j": 5321.5, "energy_ratio_vs_A0": 3.102, "gpu_peak_memory_gib": 7.24, "gpu_memory_residency_gib_s": 228.7, "gpu_utilization_integral_s": 22.17 } }, "marginal_yield": { "A0->A1": { "allocated_device_time_s": null, "device_energy_j": 0.0, "wall_time_s": null }, "A1->A2": { "allocated_device_time_s": null, "device_energy_j": 0.0, "wall_time_s": 0.0 }, "A2->A3": { "allocated_device_time_s": null, "device_energy_j": 0.00021406648843853404, "wall_time_s": 0.008315919866432606 }, "A3->A4": { "allocated_device_time_s": null, "device_energy_j": null, "wall_time_s": null }, "A4->A5": { "allocated_device_time_s": null, "device_energy_j": null, "wall_time_s": null } } }, "eml_interpretation": "The cost side of the scaffolding response curve is real and steep; the quality side is flat because the tasks were already solved at A0 and because the quality axis was confounded (RST-2026-0102). This is one point on the 'no gap' side of F4 with almost no weight: it neither supports nor refutes the scaffolding-separation hypothesis on non-trivial tasks. The A3/A4 0.667 is not a gain: the aborted CON-003 trials dropped out of the quality denominator and the surviving mean rose.", "eml_limitations": [ "quality_n is 4 (A0–A2, A5) or 3 (A3, A4) per condition because CODE-001 quality is unavailable and three trials aborted — means over 3–4 values.", "Device-measured GPU energy at ~24 % sampling overhead; not marginal energy." ], "eml_ai_collaborators": [ "Aletheia (GPT-5.6 Sol, OpenAI ChatGPT) — 2026-09-07 diagnostic", "Splice (Claude Code, Anthropic) — execution and RESULT note" ], "eml_authors": [ "Neo.K (EveMissLab)" ] }, "canonical_url": "https://evemisslab.com/ai/results/RST-2026-0101/", "json": "/ai/results/RST-2026-0101/index.json", "relations": [ { "id": "REL-2026-0486", "predicate": "qualifies", "source": "RST-2026-0101", "target": "THY-2026-0109", "status": "ACTIVE" }, { "id": "REL-2026-0487", "predicate": "qualifies", "source": "RST-2026-0101", "target": "CLM-2026-0104", "status": "ACTIVE" }, { "id": "REL-2026-0485", "predicate": "produces", "source": "EXP-2026-0103", "target": "RST-2026-0101", "status": "ACTIVE" }, { "id": "REL-2026-0490", "predicate": "qualifies", "source": "RST-2026-0102", "target": "RST-2026-0101", "status": "ACTIVE" } ], "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 } }