PrimeScientist epistemic report

Type: agentic-system-analyses/types/agentic-system-epistemic-report.md

Source-and-claim boundary

The question is what the shipped research-search workflow can acquire, conjecture, check and license for later use. Scope and dependencies are see boundary; evidence identities are see Source register. SRC-1 supplies implementation, doctrine/design and reported operation, not observed execution or causal evidence. External coding-agent and provider internals are excluded. No execution was performed.

The operational loop is score-directed experimentation. The consequential warrant claim is EPI-CLM-score-correctness. The README describes replication scored by RAGChecker F1; it does not itself establish that accepted scientific discoveries are produced. The reflector's stronger correctness language requires checking what is actually scored.

Coverage distinguishes direct inspection in this job from supplied findings. All paths below are SRC-1 at the reviewed commit. Supporting task/preparation files remain included but unassessed; this is not a system-complete negative about knowledge production.

Entry point or operation	Source path	Coverage and records, or limit
Benchmark dispatch	benchmarks/registry.py	Direct read: AutoLab/FIRE-Bench shipped; optional terminal_bench unavailable. No inference about its evaluators.
Tree CLI, setup, repeated execution, skip-evaluation, pruning	run_search.py	Direct reads of bootstrap, pruning, node runner and result disposition; CLI option search. See RT-RTE-search-execution, RT-RTE-plan-admission. Synthetic skip-evaluation packets are not checked results.
Selection, reload and Q accumulation	search/tree.py	Supplied findings, not independently reread: RT-OBJ-stats, RT-BAP-score-selector.
Reflector prompts, brief generation, insight copying	search/reflector.py	Direct reads of FIRE-Bench/proposal prompts and brief/reflection bodies; insight-write search. Session and initialization findings supplied: RT-RTE-plan-admission. No verified cross-task insight-production loop.
Fresh/inherited worker, Codex/OpenHands context	benchmarks/fire_bench/agents/codex/run.py, benchmarks/fire_bench/agents/codex/run_inherit.py, benchmarks/fire_bench/agents/openhands/run.py, benchmarks/utils.py	Supplied routes: RT-BAP-plan-worker, RT-RTE-search-execution. Model interpretation and internal tools uninspected.
AutoLab verifier/container dispatch	benchmarks/autolab/__init__.py	Reward/error helper search plus supplied RT-RTE-score-evaluation. Docker/enroot equivalence and other task oracles not independently assessed.
Concrete correctness/performance check	benchmarks/autolab/tasks/gaussian_blur/tests/test.sh, benchmarks/autolab/tasks/gaussian_blur/tests/verify_correctness.py	Direct complete reads: EPI-RTE-gaussian-check. One task witness, not all AutoLab correctness.
FIRE-Bench scoring adapter and information withdrawal	benchmarks/fire_bench/__init__.py	Direct evaluate/attachment reads: EPI-RTE-score-attachment.
Log extraction and core-idea generation	benchmarks/fire_bench/eval/RAGChecker/utils.py	Direct complete function reads: EPI-RTE-conclusion-extraction.
Reference checking, metric computation, evaluator CLI, optional error analysis	benchmarks/fire_bench/eval/RAGChecker/eval.py, benchmarks/fire_bench/eval/RAGChecker/ragchecker/evaluator.py, benchmarks/fire_bench/eval/RAGChecker/ragchecker/computation.py	Direct scoring/error-analysis/CLI bodies and extraction/check/precision/recall/F1 functions: EPI-RTE-reference-check, EPI-RTE-error-analysis. Low-level extractor/checker provider behavior uninspected.
Linear keep/revert, replay/history	run_vanilla.py	CLI search and supplied RT-RTE-vanilla-retention.
Paper/plan preparation	benchmarks/fire_bench/benchmark/plan_generator.py, benchmarks/fire_bench/benchmark/tree_parser.py	CLI search only; model-mediated preparation bodies unassessed. Prevents complete characterization of imported task lineage and preparatory conjecture/checking.
Task utility calls, other tests, task instructions/references	benchmarks/fire_bench/utils/, benchmarks/fire_bench/benchmark/papers/, benchmarks/autolab/tasks/	Included opaque alternatives. Other task checks, utility model calls and initial reference provenance unassessed; prevents exhaustive evaluator validity and scientific-method conclusions.

Missing generated plans, candidate traces, result artifacts and acceptance decisions prevent identifying actual conjectures, actual criticism, acceptance and integration. Missing deployment/model revisions prevent weight-fixity conclusions. Missing interventions prevent benefit and component-level attribution. Available but unread supporting files are inspection limits, not access gaps.

Epistemic-object inventory

Object ID	Candidate truth-apt content or none	Claimed role	Evidence source ID and local anchor	Gap/limit
RT-OBJ-skill	Possible hypotheses, expected outcomes and methods; actual content not determinable	see record	see record	Plans are guidance, not licensed findings.
RT-OBJ-sandbox	Mixed code, data and possible experimental outcomes	see record	see record	Successful retained code is not an explanation of its success.
RT-OBJ-stats	Numeric aggregates of returned scores	see record	see record	Q incorporates descendants; neither Q nor P is a truth probability.
EPI-OBJ-prior	Requested hypothesis, rationale, expected improvement and risks	see record	see record	Generated content unobserved; numeric estimate is a distinct symbolic consumer path.
EPI-OBJ-packet	Scores and benchmark-specific diagnostics about an attempt	see record	see record	Zero can reflect missing evaluation, not falsity.
EPI-OBJ-log-brief	Selected agent narrative and tool/environment reports	see record	see record	Omits middle evidence; full log remains reachable.
EPI-OBJ-core-idea	Generalized candidate conclusion	see record	see record	Source scope/numbers/methods are deliberately omitted.
EPI-OBJ-gt-answer	Imported expected answers to named task questions	see record	see record	Initial source warrant unknown; reference status is not independent truth verification.

Prior text, diagnostic briefs and evaluation packets have different checks and consumers; they are separated above rather than treated as one homogeneous truth store. Metric intermediates belong to EPI-RTE-reference-check. Their checks and consumption are separated in the ledger below.

Authority-route ledger

Rows split functions even when one supplied container record owns several. see delegates the record's fields rather than redeclaring them. No observed result is claimed. License is the report's bounded assessment, distinct from operational continuation.

Route ID	Route function	Architectural status	Object/candidate ID	Content/update relation	Transition or check target	Evaluator/condition and domain	Activation and timing	Possible or observed result	Implemented force	Epistemic authority and scope	Operational authority: behavior permitted, blocked, or changed	Behavioral-authority path: consumer, channel, force, horizon	Evidence source ID and local anchor	Claim IDs or none	Mismatch marker or none	Gap/limit
RT-RTE-plan-admission	content transformation	implemented	RT-OBJ-skill	truth-apt transformation: indeterminate	Diagnostic inputs to successor hypothesis/plan	see record	see record	see record	Requested model interpretation	Candidate only; no observed proposition to classify as entailed or ampliative	Subsequent proposal can enter worker guidance	see RT-BAP-plan-worker	see record	none	none	Prompt examples of new hypotheses do not individuate generated claims.
RT-RTE-plan-admission	operational admission/selection/consumption	implemented	RT-OBJ-skill	no content change	Proposal existence/prior to selectable child	see record	see record	see record	Filesystem existence and numeric prior handling	No semantic plan warrant	Enables a plan before scientific checks	see record	see record	none	none	This is not evidence-consuming claim acceptance.
EPI-RTE-conclusion-extraction	content transformation	implemented	EPI-OBJ-core-idea	truth-apt transformation: indeterminate	Log fragment to generalized conclusion	see record	see record	see record	Evaluator consumes transformed narrative	Candidate source warrant degraded; semantic preservation unestablished	Determines what receives F1 credit	see record	see record	EPI-CLM-score-correctness	scope-loss	Concrete quantities and methods cannot receive direct checking here.
EPI-RTE-reference-check	check/evidence production	implemented	EPI-OBJ-core-idea, EPI-OBJ-gt-answer	no content change	Extracted claims versus reference, both directions	see record	see record	see record	Produces model judgments	Reference-relative agreement, conditional on faithful extraction and judgment	Supplies score evidence, not disposition itself	see record	see record	EPI-CLM-score-correctness	reference-not-world	No experiment/replay audit in this check.
EPI-RTE-reference-check	content transformation	implemented	RT-OBJ-stats	truth-apt transformation: entailed derivation	Judgment arrays to precision/recall/F1	see record	see record	see record	Fixed arithmetic	Arithmetic from supplied labels only; their truth is not established	Supplies scalar for adapter	see record	see record	none	none	Model entailment labels are not formal proofs.
EPI-RTE-score-attachment	content transformation	implemented	RT-OBJ-stats	truth-apt transformation: non-ampliative reshaping	Evaluation representation to normalized packet metrics	see record	see record	see record	Parsing, normalization, diagnostic exclusion	Carries metric meaning if attachment succeeds; no extra warrant	Driver receives scores without reference-derived diagnoses	see record	see record	none	none	Position matching and regex failure constrain lineage.
EPI-RTE-gaussian-check	check/evidence production	implemented	RT-OBJ-sandbox	no content change	Gaussian output on fixed image and benchmark time	see record	see record	see record	Exit status and reward generation	Pixel agreement on specified test; timing conditional on binary report	Correctness failure blocks performance scoring	see record	see record	none	none	Not general Gaussian correctness or trustworthy speed on all inputs.
RT-RTE-search-execution	disposition/acceptance	implemented	RT-OBJ-sandbox	no content change	Best repeated-run packet and branch score versus parent Q	see record	see record	see record	Fixed comparison; score-pruning	Acceptance for continued search only, not acceptance of explanatory/scientific claim	Hides weak branches; eligible branches remain usable	see RT-BAP-score-selector	see record	none	none	Maximum-over-repeats is not an uncertainty estimate; parent Q is aggregate.
RT-RTE-search-execution	retention	implemented	RT-OBJ-sandbox, RT-OBJ-stats	no content change	Packet/workspace to durable node state	see record	see record	see record	File persistence, including pruned packets	Retention adds no claim acceptance	Later reload/reflection/inheritance remains possible	see record	see record	none	none	Pruning withdraws normal branch use, not stored evidence or already executed actions.
RT-RTE-plan-admission	behavior/policy adaptation	implemented	RT-OBJ-skill	non-truth-apt policy/content update: task guidance and prior	Result-conditioned proposal request to later guidance	see record	see record	see record	Model guidance plus symbolic selection	No demonstrated improvement or new knowledge follows	Can alter later selected procedure	see RT-BAP-plan-worker	see record	none	none	Actual evidence-response and worker compliance unobserved.
RT-RTE-vanilla-retention	disposition/acceptance	implemented	RT-OBJ-sandbox	no content change	New code versus best score	see record	see record	see record	Strict improvement comparison	Accepted as next seed under benchmark objective	Keeps/reverts best workspace	see record	see record	none	none	Not framework improvement or scientific claim acceptance.
RT-RTE-vanilla-retention	retention	implemented	RT-OBJ-sandbox	no content change	Iteration packets and selected workspace	see record	see record	see record	Persistence and history replay	No added warrant	Later history and best workspace seed another attempt	see record	see record	none	none	Rejected attempt evidence persists; replacement is not transactional.
EPI-RTE-error-analysis	check/evidence production	implemented	EPI-OBJ-core-idea	truth-apt transformation: indeterminate	False-positive/negative claims to proposed causal diagnosis	see record	see record	see record	None in frozen CLI dispatch	No active diagnostic license	Disabled branch; no corrective consumer	see record	see record	none	disabled-analysis	Exists as callable helper, but ordinary main sets flag false.

Route ID: RT-RTE-plan-admission Route function: content transformation Architectural status: implemented Object/candidate ID: EPI-OBJ-log-brief Content/update relation: truth-apt transformation: non-ampliative reshaping Transition or check target: see EPI-OBJ-log-brief Evaluator/condition and domain: fixed head/tail code rule, not truth evaluation. Activation and timing: before reflection, see RT-RTE-plan-admission. Possible or observed result: see EPI-OBJ-log-brief. Implemented force: diagnostic input delivery. Epistemic authority and scope: preserves selected lines, not complete evidence coverage or endorsement. Operational authority: can inform successor planning; no new enforced criterion. Behavioral-authority path: see RT-RTE-plan-admission. Evidence source ID and local anchor: SRC-1, search/reflector.py; passage see EPI-OBJ-log-brief. Claim IDs: none Mismatch marker: none Gap/limit: actual diagnostic use unobserved; full log remains reachable.

Route ID: RT-RTE-plan-admission Route function: retention Architectural status: implemented Object/candidate ID: RT-OBJ-skill, EPI-OBJ-prior Content/update relation: no content change Transition or check target: prospective guidance/rationale to durable child files. Evaluator/condition and domain: see RT-RTE-plan-admission. Activation and timing: see RT-RTE-plan-admission. Possible or observed result: see RT-RTE-plan-admission. Implemented force: durable availability. Epistemic authority and scope: persistence before semantic acceptance; no added warrant. Operational authority: selected plans guide later workers and rationales are available to later reflectors. Behavioral-authority path: see RT-RTE-plan-admission. Evidence source ID and local anchor: see RT-RTE-plan-admission. Claim IDs: none Mismatch marker: none Gap/limit: actual authorship/content use unobserved.

Within the inspected driver/evaluator routes, no separate lifecycle-integration function for accepted scientific claims was found. Search retention and plan reuse precede any such acceptance. Unassessed preparation/task paths prevent extending that finding to every shipped operation.

System-claim versus route comparison

Claim ID	Claimed operation or warrant	Claim source ID/anchor and evidence layer	Doctrine/design support	Implemented route IDs	Observed-run support	Causal support and design limits	Supported conclusion	Mismatch/unknown
EPI-CLM-score-correctness	see record	see record	see record	EPI-RTE-conclusion-extraction, EPI-RTE-reference-check, EPI-RTE-score-attachment	None supplied	No intervention; reference-relative metric cannot identify experimental validity or mechanism	A score can indicate model-assessed agreement of generalized narrative with benchmark answer	Correctness language exceeds the checked domain.

RT-CLM-budget-stop concerns operational budget enforcement, not truth warrant. Its qualifications remain see record; this report does not convert resource controls into epistemic guarantees.

Bounded conclusion

PrimeScientist retains plans, code/workspaces, outcomes, numeric statistics and diagnostics, then uses them for symbolic selection and model-guided successor planning. These are independently supported operational feedback paths, not merely file storage. Force differs: numerical scores enforce branch availability and affect sampling; plans and rationales are advisory/model-interpreted. Repeated operation and resumes extend their horizon beyond one worker call. See RT-RTE-search-execution, RT-RTE-plan-admission, RT-BAP-plan-worker, RT-BAP-score-selector.

FIRE-Bench acquires benchmark references whose initial warrant is unknown. It extracts a log fragment, asks a model to strip numerical/method/artifact detail, extracts claims and checks reference-relative agreement. It does not establish the truth of the original experiment, faithfully encoded scope, explanation, replay safety or transfer. Arithmetic F1 is derivable from labels; those labels remain model judgments. Attachment preserves normalized metrics but deliberately withholds ground-truth-derived error lists from the reflector. The optional file-search error analysis cannot repair this gap in ordinary execution: it is disabled and has no correction consumer. See EPI-RTE-conclusion-extraction, EPI-RTE-reference-check, EPI-RTE-score-attachment, EPI-RTE-error-analysis.

AutoLab supplies a different kind of evidence. The inspected Gaussian task compares output against a deterministic reference on one fixed input, gates timing on that check and computes a reward from three binary-reported times. This can license the specified test result, not universal functional correctness or verified general speed. Other task evaluators may differ and remain unassessed. See EPI-RTE-gaussian-check.

Tree and vanilla decisions accept artifacts for continued benchmark search: the former prunes below parent aggregate Q, and the latter requires strict improvement over the best score. These name operational criteria and intended use, but neither records evidence-consuming acceptance of an individuated ampliative scientific claim. Requested hypotheses/criticism provide candidate-making capacity; no actual generated claim here establishes conjecture, content-directed criticism, acceptance or lifecycle integration. Retention alone does not close those phases.

The runtime's independent assessments remain bounded: theory formulation/consumption are afforded, criticism is requested, reflection has a wired representation-and-guidance path, internal scheduling is computational, and exercised learning/self-improvement remain uninspected. No accessible weight-change evidence resolves provider-parametric learning or fixity: see RT-CMP-coding-model, RT-CMP-reflector-model, RT-CMP-eval-model, RT-CMP-ragchecker-models. No system-wide score or negative verdict follows from these separate findings.

Shared records

Operative objects

EPI-OBJ-prior

Label: Proposal prior Part of: RT-RTE-plan-admission

Source-native identity: child prior.json, a durable filesystem JSON object produced within the parent proposal route. Its hypothesis/rationale/changes/risks are natural-language guidance to later reflectors; estimate is symbolic numeric input to bootstrap and selection. It is not the plan file RT-OBJ-skill: it describes why and what to change, whereas the skill guides execution. Different consumer paths are retained, not inferred from the JSON substrate. SRC-1, search/reflector.py and run_search.py, doctrine/design and implementation. Passage and theory-condition findings are see RT-RTE-plan-admission. The inspected bootstrap defaults/clamps only the estimate; no semantic acceptance of hypothesis/rationale is established. Pruning summaries can preserve its text for later proposer guidance.

EPI-OBJ-packet

Label: Evaluation packet Part of: RT-RTE-score-evaluation

Source-native identity: evaluator packet, persisted as node packet.json; an output object contained in the parent evaluation route, not a second declaration of that route. JSON filesystem substrate mixes symbolic scores/run identifiers with natural-language error/detail fields. Numeric consumers are driver/pruning/statistics; diagnostic consumers are later reflectors. Unlike RT-OBJ-stats, this is a particular run's packet, not a descendant-averaged statistic. SRC-1, run_search.py, benchmarks/fire_bench/__init__.py, implementation. Evidence passage and adapter criteria are see RT-RTE-score-evaluation; score attachment limits are see EPI-RTE-score-attachment. Ordinary FIRE-Bench packet excludes reference-derived diagnosis; AutoLab can expose verifier diagnostics. Retention does not endorse each reported field as scientific truth.

EPI-OBJ-log-brief

Label: Log brief Part of: RT-RTE-plan-admission

Source-native identity: node log_brief.log; natural-language/tool-result diagnostic excerpt on filesystem, produced inside the parent's reflection-input preparation route. It is distinct from RT-OBJ-skill: retrospective evidence presented to a proposer, not prospective instructions. SRC-1, search/reflector.py, implementation. Default 100-head/500-tail behavior and hidden-full-log access are see RT-RTE-plan-admission and supplied runtime context account. The local complete function read establishes a deterministic non-ampliative selection: for lines L1–L8 with head=2 and tail=3, the function retains L1/L2 and L6/L7/L8 with an omission notice for three middle lines. It preserves retained lines but reduces available evidential coverage; it does not evaluate their truth. The full log remains available for explicit inspection. This is a lineage/context-delivery function within the plan route, not epistemic acceptance.

head_block = lines[:head] tail_block = lines[-tail:] omitted = len(lines) - head - tail --- search/reflector.py

EPI-OBJ-core-idea

Label: Core idea

Source-native identity: core_idea in eval_single_log; natural-language content, held in a Python string and RAGResults response field, then evaluator output. Distinct from RT-OBJ-skill: this is a result narrative, not prospective guidance; no supplied object counterpart after comparison. SRC-1, benchmarks/fire_bench/eval/RAGChecker/eval.py and benchmarks/fire_bench/eval/RAGChecker/utils.py, implementation and doctrine/design. Its producer is the extraction model; its consumers are RAGChecker claim extraction/checking, not the ordinary packet's agent_conclusion field.

core_idea = extract_core_idea(raw_conclusion, client, eval_model) --- benchmarks/fire_bench/eval/RAGChecker/eval.py

EPI-OBJ-gt-answer

Label: Ground truth answer

Source-native identity: gt[task], paired with query[task]; natural-language expected-answer content in the shipped gt dictionary, copied to RAGResults gt_answer. Distinct from the core idea and RT-OBJ-skill; closest supplied route is RT-RTE-score-evaluation, not an object counterpart. SRC-1, benchmarks/fire_bench/eval/RAGChecker/utils.py (definition location searched) and benchmarks/fire_bench/eval/RAGChecker/eval.py (consumer directly inspected), implementation. Full reference provenance not assessed. Acquired expected answer, not a claim produced by this attempt.

"gt_answer": f"{gt[task]}", "response": f"{core_idea}", --- benchmarks/fire_bench/eval/RAGChecker/eval.py

Routes

EPI-RTE-conclusion-extraction

Label: Conclusion extraction Part of: RT-RTE-score-evaluation

Endpoints: agent log → heuristic fragment → model core idea → RAGChecker input. Owner: evaluator utility code and extraction-model service. Local fragment selection is symbolic; core-idea generation is natural-language interpretation by RT-CMP-eval-model. SRC-1, benchmarks/fire_bench/eval/RAGChecker/utils.py, implementation and doctrine/design. This separates the transformation part from its parent's checking.

• implementation conclusion status: wired
• operation conclusion status: uninspected
• Immediate return: extracted string or None, then model response string.
• Later read-back: transformed response enters saved evaluator representations; ordinary packet excludes agent conclusion. No later diagnosis reuse established.
• Delegated visibility: extraction model receives selected fragment, not full experiment data; checker receives generalized response.
• Selection predicate: last OpenHands match, otherwise timestamp slice, otherwise last-line JSON result; core-idea prompt then controls omission.
• Invalidation or expiry: inapplicable — current scoring transform; no withdrawal or expiry policy for saved evaluator outputs shown.
• Activation or effect: transformation defines the scored text; actual semantic fidelity and provider compliance unobserved.
• Evidence limits: external model processing opaque; neither faithful non-ampliative summary nor ampliative conjecture established for an actual output.

Concrete implementation deduction without target execution: with timestamps [2025-09-19T10:05:41] A, [2025-09-19T10:05:42] B, [2025-09-19T10:05:43] C on successive lines and no OpenHands match, the timestamp branch selects the first two timestamped lines and excludes C. Despite its comment saying second-last boundary, the code uses the last timestamp. Thus the function name does not guarantee final-answer isolation.

start = timestamps[-3].start() end = timestamps[-1].start() extracted = content[start:end].strip() --- benchmarks/fire_bench/eval/RAGChecker/utils.py

"omitting all concrete values, specific numbers, background details, methods, " "file names, or references to artifacts. " --- benchmarks/fire_bench/eval/RAGChecker/utils.py

The prompt's no-inference instruction is a counterweight, not a semantic-preservation check:

"DO NOT infer any detail, context information, or background knowledge that is not mentioned " "in the original conclusion." --- benchmarks/fire_bench/eval/RAGChecker/utils.py

EPI-RTE-reference-check

Label: Reference check Part of: RT-RTE-score-evaluation

Endpoints: core idea/reference/query → model-extracted claims → checker labels in both directions → metric means/harmonic mean. Owner: vendored evaluator, with external extractor/checker services; model properties see RT-CMP-ragchecker-models. SRC-1, benchmarks/fire_bench/eval/RAGChecker/ragchecker/evaluator.py, benchmarks/fire_bench/eval/RAGChecker/ragchecker/computation.py, implementation. Truth-apt target is agreement of answer claims with reference content, not whether experiments happened or data entail the conclusion. Human-authored benchmark answer is the oracle; initial provenance unknown. Computational code schedules checking and aggregates model decisions; no current human veto. Mode: bounded benchmark trials, triggered by completed log scoring. It produces evidence, not an acceptance decision.

• implementation conclusion status: wired
• operation conclusion status: uninspected
• Immediate return: RAGResults with extracted claims, checker labels and metrics.
• Later read-back: evaluator results persist as repr strings; normalized scores enter driver packets/Q and later reflection.
• Delegated visibility: claim extractor sees query/text; checker sees extracted claims, query and opposite answer text. Retrieved context is empty in the shipped scoring entry.
• Selection predicate: task identifies query/reference; metrics specify required checking directions.
• Invalidation or expiry: inapplicable — returns judgment/metric, not retention policy.
• Activation or effect: metric is consumed by adapter and score selector; model judgment reliability unobserved.
• Evidence limits: lower-level extractor/checker internals unassessed; no independent validation of reference, extraction coverage or entailment labels.

claims = [ret.response_claims for ret in results] references = [ret.gt_answer for ret in results] --- benchmarks/fire_bench/eval/RAGChecker/ragchecker/evaluator.py

claims = [ret.gt_answer_claims for ret in results] references = [ret.response for ret in results] --- benchmarks/fire_bench/eval/RAGChecker/ragchecker/evaluator.py

if isinstance(checking_results, str): return checking_results == "Entailment" --- benchmarks/fire_bench/eval/RAGChecker/ragchecker/computation.py

result.metrics[metrics.f1] = 2 * precision * recall / (precision + recall) --- benchmarks/fire_bench/eval/RAGChecker/ragchecker/computation.py

This is entailed arithmetic conditional on checker labels and nonzero means, not formally certified source truth.

EPI-RTE-score-attachment

Label: Score attachment Part of: RT-RTE-score-evaluation

Endpoints: newly saved evaluation file → regex/record matching → packet scores without reference-derived diagnoses → driver. Owner: FIRE-Bench adapter. SRC-1, benchmarks/fire_bench/__init__.py, implementation. It separates lineage and information-withdrawal behavior from the parent's evaluator. This does not revise the parent's identity.

• implementation conclusion status: wired
• operation conclusion status: uninspected
• Immediate return: run records with precision/recall/F1 normalized from 0–100 to 0–1, or empty scores.
• Later read-back: packet scores enter tree statistics and reflector packets; diagnostic claim lists are not exposed through this packet route.
• Delegated visibility: driver/reflector sees normalized scores and empty agent_conclusion, not false-positive/negative claim content.
• Selection predicate: new result files; optional error-analysis log-path match, otherwise index matching; metric regex must match.
• Invalidation or expiry: inapplicable — information omission occurs during packet construction, not deletion of stored evaluator files.
• Activation or effect: primary_score consumes F1, defaults absent to zero; poor/missing attachment can affect pruning/selection without truthful negative evidence.
• Evidence limits: evaluator subprocess uses check=False; missing/malformed/mismatched results do not establish experimental failure or falsity.

rec["agent_conclusion"] = "" rec["false_positives"] = [] rec["false_negatives"] = [] --- benchmarks/fire_bench/__init__.py

return float(packet.get("score", {}).get("f1") or 0.0) --- benchmarks/fire_bench/__init__.py

This counters the possible inference that detailed benchmark contradiction evidence reaches the reflector. Files remain accessible; packet-level withholding is not an access-control guarantee.

EPI-RTE-gaussian-check

Label: Gaussian check Part of: RT-RTE-score-evaluation

Endpoints: submitted blur binary → fixed-image comparison → benchmark timing → reward JSON → AutoLab packet. Owner: task test script/reference Python program; computational admission, human contribution is shipped test/reference/constants. SRC-1, benchmarks/autolab/tasks/gaussian_blur/tests/test.sh, benchmarks/autolab/tasks/gaussian_blur/tests/verify_correctness.py, implementation. Mode: bounded benchmark trial after build. Oracle: separable Gaussian reference, five passes, sigma 3, radius 8, clamp-to-edge, deterministic 256×256 input, tolerance 4. This check has genuine content-sensitive evidence independent of the worker's narrative, so a blanket claim that all evaluation is model judgment would be false.

• implementation conclusion status: wired
• operation conclusion status: uninspected
• Immediate return: correctness exit code and reward/correctness/metric/speedup JSON; build/correctness failure yields zero.
• Later read-back: AutoLab packet and verifier diagnostics reach driver/reflector; retained workspace can seed another attempt.
• Delegated visibility: verifier receives compiled workspace and protected task tests; driver receives reward/detail, not an independently repeated measurement.
• Selection predicate: fixed test input first; performance benchmark is 4096×4096 with median of three binary-reported times.
• Invalidation or expiry: inapplicable — this check reports an attempt; later artifact replacement belongs to driver.
• Activation or effect: bad correctness blocks timing reward; reward subsequently ranks/prunes artifacts, not the proposed mechanism.
• Evidence limits: finite input and tolerance; performance parses binary output rather than independent wall-clock measurement. No measured execution or resistance to benchmark-specific behavior established.

if ! python3 /tests/verify_correctness.py 2>&1; then echo "Correctness check FAILED." write_reward 0.0 false null null --- benchmarks/autolab/tasks/gaussian_blur/tests/test.sh

if diff > TOLERANCE: bad_count += 1 --- benchmarks/autolab/tasks/gaussian_blur/tests/verify_correctness.py

OUTPUT=$(/app/blur "$INPUT" - 4096 4096 2>/dev/null) T=$(echo "$OUTPUT" | sed 's/.time=([0-9.]).*/\1/') --- benchmarks/autolab/tasks/gaussian_blur/tests/test.sh

Given a reported median of 0.25 seconds, the script's baseline 12/reference 0.25 yields speedup 48 and reward 0.5, not raw throughput ratio 48. This implementation deduction bounds the README's shorthand. Correctness success still does not warrant that performance field against a deceptive reporter.

EPI-RTE-error-analysis

Label: Error analysis Part of: RT-RTE-score-evaluation

Endpoints: false-positive/negative labels plus paper/log → temporary provider vector store → model/file_search → parsed error diagnoses → optional saved analysis. Owner: evaluator CLI/helper; external model is the same configured eval_model as RT-CMP-eval-model. SRC-1, benchmarks/fire_bench/eval/RAGChecker/eval.py, implementation and doctrine/design. Distinct dormant part of the evaluator container, omitted from the supplied operational route description. Target: why a reference-relative claim is wrong/missed; possible diagnoses are themselves candidate truth-apt causal accounts. No causal comparison validates them. Main sets a literal false flag, with no enabling CLI argument in the inspected parser. No source change or target execution was made.

• implementation conclusion status: wired
• operation conclusion status: uninspected
• Immediate return: helper can return parsed FP/FN diagnoses; disabled main branch produces none.
• Later read-back: uninspected — optional saved analysis has no implemented corrective consumer in the inspected driver; adapter suppresses diagnosis fields.
• Delegated visibility: helper registers paper/log in temporary vector store and exposes file_search with max_num_results 5 to eval_model.
• Selection predicate: only if local do_error_analysis flag is true; per FP/FN statement model call. It is false in frozen main.
• Invalidation or expiry: vector store requests one-day expiry from last activity; uploaded-file cleanup not established.
• Activation or effect: no active force in ordinary CLI path and no automatic revision/withdrawal consumer found in inspected adapter/driver.
• Evidence limits: callable helper exists, so absence of any diagnostic capacity would be too strong; successful provider indexing, grounding and causal diagnosis unobserved.

do_error_analysis = False

if do_error_analysis: --- benchmarks/fire_bench/eval/RAGChecker/eval.py

"type": "file_search", "vector_store_ids": [vs_id], "max_num_results": 5, --- benchmarks/fire_bench/eval/RAGChecker/eval.py

expires_after={"anchor": "last_active_at", "days": 1}, --- benchmarks/fire_bench/eval/RAGChecker/eval.py

Claims

EPI-CLM-score-correctness

Label: Score correctness

Claimed operation: FIRE-Bench reflector prompt treats packet reward as correctness of the agent's run conclusion and instructs reliance on score over narrative. SRC-1, search/reflector.py, doctrine/design. No counterpart after comparison with RT-CLM-budget-stop, which concerns resources. Closest supplied mechanism is RT-RTE-score-evaluation. Claim is bounded by extraction, generalization and reference-relative model evaluation rather than verified experiment truth.

{pruned_section} {node_rel}/packet.json — reward score (precision/recall/f1) and run metadata, the reward score symbolizes the correctness of agent run conclusion. --- search/reflector.py

— trust packet.json score, not the agent's narrative. --- search/reflector.py