ExperimentEXP-2026-0008v0.1

PACC-Lab v0.1 — E0–E4: first micro-witness

Three primitive-level non-probabilistic systems (N0 signed support, N1 ordinal tournament, N2 signed graph) integrate evidence over four hidden hypotheses next to an exact Bayesian reference. All three pass the Level-3 micro criteria — held-out JS ≤ 0.0101, update JS ≤ 0.0042, intervention JS ≤ 0.0058, action agreement ≥ 0.957 — in both uniform and heterogeneous evidence quality, with shuffled-target controls around 0.31–0.33. The redundancy diagnostic collapses N0 and N1 into one exact reparameterization family, leaving two independent families against a PACC-A minimum of three.

Research status: STABLE the current conclusions are relatively stable
Evidence level: E3 Repeated experiment
Result: MIXED
Data basis: SYNTHETIC Synthetic data and theoretical reasoning. Many now treat synthetic data as if it were real; this laboratory says the opposite deliberately — until a real hybrid model exists, an inference is only an inference, and theoretically possible is not actually possible.
Version: 0.1
Updated: 2026-09-08
Created: 2026-09-08
Domain: Model Representation, Evaluation, Formal AI
Program: PRG-2026-0001 Adaptive Epistemic Systems
Authors: Neo.K (EveMissLab)
AI collaborators: Sol (GPT-5.6, OpenAI ChatGPT)

Hypothesis

hypothesis: A system whose canonical state and update rules do not require probability can converge toward a Bayesian reference in behaviour, held-out state representation and update dynamics.

Setup

model_ids: MOD-2026-0001 N0 — signed support
MOD-2026-0002 N1 — ordinal tournament
MOD-2026-0003 N2 — signed graph
MOD-2026-0004 N3 — constraint competition
MOD-2026-0005 Bayesian reference (exact posterior / Beta-Bernoulli / joint common-cause / HMM)
dataset_ids: DAT-2026-0001 PACC synthetic evidence worlds
benchmark_ids: BEN-2026-0001 PACC micro-lab protocol v0.1 (frozen gates)
software_environment: Python; deterministic seeded generators; no network, no LLM.

Runs

run_count

random_seeds

20260908
8 fixed secondary seeds (post-hoc)

controls

shuffled-target mapping
constant prediction
broken composition (v0.6+)
target-local refit (v0.7+)

metrics

verdict

PRELIMINARY_PACC_B_R_D_MICRO_WITNESS_WITHOUT_STRONG_ATTRACTOR_CLOSURE

e0_purity

true

uniform

N0

agreement: 0.983073
heldout_js: 0.000192
update_js: 5.2e-05
intervention_js: 6.1e-05
shuffled_js: 0.322816

N1

agreement: 0.983073
heldout_js: 0.000192
update_js: 5.2e-05
intervention_js: 6.8e-05
shuffled_js: 0.312444

N2

agreement: 0.957465
heldout_js: 0.008053
update_js: 0.003872
intervention_js: 0.005756
shuffled_js: 0.309444

heterogeneous

N0

agreement: 0.983073
heldout_js: 0.002878
update_js: 0.000559
intervention_js: 0.000645

N2

agreement: 0.958767
heldout_js: 0.010109
update_js: 0.004186
intervention_js: 0.004187

independent_families

strong_attractor_minimum

secondary_8_seed_pass_rate

1.0

Interpretation

interpretation: Non-probabilistic primitives can exhibit probability-like state and update structure in controlled micro-tasks; two independent convergent families are not enough to establish a computational attractor. Under uniform reliability additive signed support is closely related to rescaled log-evidence accumulation — the heterogeneous stress makes the result less trivial, not deeply equivalent.

Limitations

limitations: Does not show probability is false, Bayesian inference unnecessary, LLM internals equivalent, non-probabilistic systems superior, or probability an observer projection.
E4 dynamic-world numbers are descriptive only (HMM hazard and decay untuned).

Reproduction

reproduction_instructions: Extract the version's FINAL bundle; python -m pytest -q; run the version's primary script with the recorded seed; docs/PACC_LAB_v0.N_RESULTS.md and docs/EXPERIMENT_PROTOCOL_v0.N.md are inside the bundle.

Results

Source	Relation	Target	Status	ID
`EXP-2026-0008` PACC-Lab v0.1 — E0–E4: first micro-witness	`produces`	`RST-2026-0006` v0.1 primary table: Level 3 for N0/N1/N2, two families	`ACTIVE`	`REL-2026-0166`

Recorded fields

completed_at: 2026-09-08

Relations

Source	Relation	Target	Status	ID
`EXP-2026-0008` PACC-Lab v0.1 — E0–E4: first micro-witness	`runs_on`	`SYS-2026-0002` PACC-Lab — micro-lab harness for the convergence conjecture	`ACTIVE`	`REL-2026-0156`
`EXP-2026-0008` PACC-Lab v0.1 — E0–E4: first micro-witness	`uses_benchmark`	`BEN-2026-0001` PACC micro-lab protocol v0.1 (frozen gates)	`ACTIVE`	`REL-2026-0157`
`EXP-2026-0008` PACC-Lab v0.1 — E0–E4: first micro-witness	`uses_dataset`	`DAT-2026-0001` PACC synthetic evidence worlds	`ACTIVE`	`REL-2026-0158`
`EXP-2026-0008` PACC-Lab v0.1 — E0–E4: first micro-witness	`uses_model`	`MOD-2026-0001` N0 — signed support	`ACTIVE`	`REL-2026-0159`
`EXP-2026-0008` PACC-Lab v0.1 — E0–E4: first micro-witness	`uses_model`	`MOD-2026-0002` N1 — ordinal tournament	`ACTIVE`	`REL-2026-0160`
`EXP-2026-0008` PACC-Lab v0.1 — E0–E4: first micro-witness	`uses_model`	`MOD-2026-0003` N2 — signed graph	`ACTIVE`	`REL-2026-0161`
`EXP-2026-0008` PACC-Lab v0.1 — E0–E4: first micro-witness	`uses_model`	`MOD-2026-0004` N3 — constraint competition	`ACTIVE`	`REL-2026-0162`
`EXP-2026-0008` PACC-Lab v0.1 — E0–E4: first micro-witness	`uses_model`	`MOD-2026-0005` Bayesian reference (exact posterior / Beta-Bernoulli / joint common-cause / HMM)	`ACTIVE`	`REL-2026-0163`
`EXP-2026-0008` PACC-Lab v0.1 — E0–E4: first micro-witness	`tests`	`THY-2026-0005` PACC conjecture — the four-level convergence ladder	`ACTIVE`	`REL-2026-0164`
`EXP-2026-0008` PACC-Lab v0.1 — E0–E4: first micro-witness	`produced`	`ART-2026-0021` PACC-Lab v0.1 E0-E4 FINAL `artifact://evemisslab/adaptive-epistemic-systems/PACC-Lab_v0.1_E0-E4_FINAL.zip`	`ACTIVE`	`REL-2026-0165`
`EXP-2026-0008` PACC-Lab v0.1 — E0–E4: first micro-witness	`produces`	`RST-2026-0006` v0.1 primary table: Level 3 for N0/N1/N2, two families	`ACTIVE`	`REL-2026-0166`
`EXP-2026-0009` PACC-Lab v0.2 — third family (N3) and adversarial evidence geometry	`extends`	`EXP-2026-0008` PACC-Lab v0.1 — E0–E4: first micro-witness	`ACTIVE`	`REL-2026-0178`

History and provenance

Canonical URL

https://evemisslab.com/ai/experiments/EXP-2026-0008/

Machine-readable

/ai/experiments/EXP-2026-0008/index.json

Snapshot

AI-SNAPSHOT-v0.1-fe85b9694a45

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