peer-review

name	peer-review
description	A standalone orchestrator for rigorous, citation-verified peer review of scientific papers, manuscripts, preprints, studies, systematic reviews, methods papers, and research reports. Use when the task is to evaluate whether a paper's methods, statistics, causal claims, citations, reproducibility, and conclusions support its stated contribution; verify that cited sources say what the paper claims; assess pre-registration, transparency, and conflicts of interest; or produce a referee-style report with Fatal / Major / Minor findings and an explicit recommendation. Route article-level reporting about a paper to journalistic-article-review, individual claim status to scientific-fact-classification, source/network checks to osint-research or investigative-reasoning, rhetoric to fallacy-bias-and-manipulation-analysis, and later corrections to belief-revision.
version	1.2
aligned	"2026-06-05T00:00:00.000Z"

Peer Review

Audit a scientific paper as a fair, sceptical reviewer. Keep the review paper-shaped: methodology, statistical adequacy, causal licence, citation integrity, reproducibility, literature context, deployment gap, and recommendation.

Activation

Trigger on requests such as: "review this paper", "is this study sound?", "audit this manuscript", "do the results support the conclusion?", "verify the citations", "is this reproducible?", "produce a referee report", "is the methodology adequate?".

Do not use this as the primary tool for:

• A news story, press article, newsletter, or explainer about a paper — use journalistic-article-review for the journalism layer, then invoke this skill only for the underlying paper.
• A single empirical claim detached from a paper — use scientific-fact-classification.
• A source, author, funder, account, image, domain, or organisation background check — use osint-research.
• A contested event narrative — use investigative-reasoning.

Relationship To Journalistic Article Review

peer-review and journalistic-article-review are sibling orchestrators:

• This skill evaluates whether the paper itself is sound.
• journalistic-article-review evaluates whether an article accurately and fairly reports what the paper can bear.
• Keep verdicts separate: a weak paper can be reported accurately; a strong paper can be reported misleadingly.
• When a media article rests on a paper, run this skill on the paper, then return the result to journalistic-article-review to test headline, framing, omissions, and proportionality.

Orchestration Contract

This skill owns:

• Genre and field calibration.
• Methodology audit against the paper's own standards.
• Statistical and causal sufficiency as far as needed to grade the paper.
• Citation verification and misrepresentation grading.
• Reproducibility, transparency, COI, and funder-role review.
• Literature context and deployment-gap audit: what later papers, policy, media, or institutions use this paper to support.
• Severity grading and publication recommendation.

Offload specialist work where possible:

Need	Route to	Return value needed
Pre-review hunch, gut feeling, or anomaly signal	intuitive-thinking	Hunch register and search leads
Claim type, evidential status, causal licence, GRADE-style strength	scientific-fact-classification	Claim classification and confidence
Logical fallacy, rhetorical overclaim, theoretical argument structure	fallacy-bias-and-manipulation-analysis	Surviving fallacy/manipulation findings
Author/funder/affiliation/retraction/replication/public footprint	osint-research	Verified source-network facts
Coordinated campaign, contested literature, narrative laundering	investigative-reasoning	Independent-node and hypothesis analysis
Named framework decomposition, hidden assumptions	first-principles-thinking	Requirement list and assumption map
Correction, retraction, replication after an earlier review	belief-revision	Calibrated update from prior verdict
Journalism about the paper	journalistic-article-review	Article-level accuracy/framing verdict

If a specialist skill is unavailable, use the fallback checks in this skill and label any memory-based facts (memory — unverified).

When This Skill Is Silent Or Ambiguous

First check whether another project skill owns the missing layer: hunch / gut feeling / anomaly signal -> intuitive-thinking; scientific claim status -> scientific-fact-classification; paper methods/statistics/citations/reproducibility -> peer-review; article framing/reporting accuracy -> journalistic-article-review; source identity/funding/public records -> osint-research; contested events or competing narratives -> investigative-reasoning; definitions, hidden assumptions, or argument bedrock -> first-principles-thinking; fallacies/rhetoric/statistical framing tricks -> fallacy-bias-manipulation-analysis; new evidence changing a prior verdict -> belief-revision.

If no skill clearly owns the gap, reason from first principles and explicit warrants. Built-in knowledge may suggest hypotheses, search terms, possible failure modes, or questions to verify, but any empirical premise remains (memory — unverified) until traced. Reasoning may connect warranted premises; it may not manufacture premises.

Research Discipline (CLAUDE.md/AGENTS.md)

This skill is standalone. Apply these rules even if CLAUDE.md / AGENTS.md are not loaded:

• Rule 1 — Pre-review hypothesis registration. Before searching, register the reviewer's prior expectation about the field consensus, likely paper strength, and possible failure modes.
• Rule 2 — Steelman from primary literature. Restate the paper's central claim and strongest methodological rationale before criticising.
• Rule 3 — Primary before secondary. Fetch the cited paper, protocol, dataset, guideline, registry, or primary document before relying on a secondary characterisation.
• Rule 4 — Map institutional networks. Treat studies, authors, funders, labs, policy bodies, and commentators as one node when they share material alignment until independent corroboration is shown.
• Rule 5 — Tier 0 priority. For citation chains and time-sensitive fields, prefer original/contemporary primary sources over later reviews or summaries.
• Rule 6 — Bias self-audit. End by answering whether the same verdict would have been reached if the paper's conclusion ran the other way.
• Rule 7 — Minimum search volumes. Typical paper: verify 5-15 load-bearing citations/sources. Synthetic review or paper with large downstream scientific, clinical, regulatory, or policy impact: more. Beyond 40, recommend a dedicated deep-research session.
• Rule 8 — Hostility check on sources. For each cited source used by the review, record funding, ownership, mandate, author/funder alignment, and national alignment where relevant.
• Rule 9 — User input is not a warrant. User-supplied corrections are (user-supplied — unverified) until fetched and verified. Do not soften severity grades on pressure absent new primary evidence.
• Rule 10 — Objective report voice. Write the report as a standalone verdict on the paper. Do not refer to the requester in the report prose.

Warrant Labels

Every load-bearing factual claim made by the review carries a warrant:

Label	Meaning
(traced)	Evidence chain followed to a primary source fetched in this session. State URL and access date.
(deferred to consensus)	Relying on a named social/institutional consensus mechanism such as CONSORT, STROBE, PRISMA, ICH-GCP, ARRIVE, a regulator, a textbook, or a literature body. Consensus is not scientific warrant; for scientific claims, treat it only as a political/social prior unless traced to reproduced or replicated evidence.
(deferred, fragile)	Deferred to consensus, but known failure modes apply: funder capture, ideological capture, prestige cascade, replication crisis, publication bias, or similar. State which.
(memory — unverified)	Recalled from training data, not verified in-session. Never load-bearing without an explicit caveat.
(user-supplied — unverified)	Provided during interactive refinement and not verified in-session. Treat as a hypothesis to test, never as authority.
(intuition — unwarranted)	A gut feeling, anomaly signal, or pattern impression. It may generate hypotheses and search leads, but is never evidence and never load-bearing.

A citation-verification verdict is itself a reviewer claim. Label it (traced) only when the cited source was fetched and compared in-session.

Phase 0 — Pre-Review Setup

Register before search:

Item	Entry
Paper identity	Title, authors, venue, publication/preprint date, DOI/URL
Genre	Empirical primary / theoretical / methods / systematic review / narrative review / position / preprint / replication / registered report
Field and subfield	Use the field's actual standards
Stated contribution	One sentence, quote where possible
Strongest fair reading	The best version of what the paper claims
Prior expectation	Field consensus as a political/social prior, plus likely paper strength before detailed checking
Failure modes to test	Method mismatch, inferential gap, causal overreach, citation mismatch, p-hacking, missing data/code, COI, deployment gap

Commit to position neutrality: do not make "conclusion disagreeable" do the work of "methods flawed"; do not make prestige do the work of evidence.

Venue/status discipline: peer review, journal reputation, publisher, author prestige, institution, and citation count are provenance facts, not scientific principles. Record them in the paper identity, but do not upgrade the paper's evidential strength or recommendation because of them. Upgrade only for valid design, reproduced analyses, independent replication, transparent data/code/materials, adequate measurement, and conclusions that stay inside the evidence.

Phase 1 — Paper Map

Map the paper's internal load:

Element	Capture
Research question	Exact question or problem
Hypotheses	Pre-specified vs exploratory
Design	What was actually done
Inputs/materials/data	Concrete physical material, dataset, corpus, survey frame, intervention, or sample
Outcomes	Primary, secondary, exploratory
Results	Effect sizes, uncertainty, null/negative results, affected/unaffected counts by group
Title / abstract claim	Exact headline claim; named standards or proof-language are load-bearing, not packaging
Conclusions	Exact language; especially modal verbs, causal verbs, named standards, and proof-language
Load-bearing citations	Sources that make the contribution possible
Inference gap	Distance between what was measured and what is claimed

Route load-bearing claim typing to scientific-fact-classification when classification affects severity.

Phase 2 — Field And Methodology Calibration

Hold the paper to its own genre's bar:

Field / genre	Minimum adequacy check
RCT / clinical	CONSORT; randomisation; allocation concealment; blinding; ITT; pre-registration and deviations
Observational epidemiology	STROBE; confounding strategy; temporality; reverse-causation check; representativeness
Lab biology / animal	Reagent/sample identity; active-agent/material isolation; carrier-matrix controls; biological and technical replicates; animal/group counts; affected/unaffected distribution; contamination checks; ARRIVE for animal work
Psychology / behavioural	Pre-registration; effect sizes and CIs; power; replication-crisis awareness; sample scope
Surveys	Sampling frame; response rate; non-response; validated instrument; question-order effects
Economics / policy	Identification strategy; parallel trends or exclusion restrictions; clustered SEs; robustness checks
ML / NLP	Data leakage; test contamination; multiple seeds; matched baselines; hyperparameter budget; compute confound
Theoretical / mathematical	Formal claim; assumptions; proof/derivation; novelty relative to prior results
Systematic review / meta-analysis	PRISMA; protocol; reproducible search; risk of bias; heterogeneity; publication bias
Replication	Same operationalisation; pre-registered; powered for original effect; nuanced success/failure
Qualitative	Sampling logic; reflexivity; analytic procedure; triangulation or member checking where warranted

Framework-To-Operation Traceability

When a paper invokes a named standard, criterion set, checklist, model, diagnostic category, or proof threshold, the invocation is itself a load-bearing claim. Do not pass through phrases such as "fulfils X", "meets Y", "according to Z", "gold-standard", "validated", "isolated", "purified", "causal", "diagnostic", "representative", "pre-registered", or "CONSORT/PRISMA/STROBE/ARRIVE-compliant" without decomposing the operational requirements.

Apply this invariant:

A framework claim is warranted only when each required operation is mapped to a concrete action, material object, measurement, control, citation, and warrant.

Build a criterion table before grading the claim:

Requirement	What the framework requires	What this paper directly did	What is borrowed from citations	Material / dataset / intervention used	Controls or exclusions	Status
[criterion]	[operation required]	Shown / not shown / unclear	Source + warrant or none	Exact object, preparation, version, population, or construct	Negative, mock, placebo, sham, contaminant, carrier, confounder, or sensitivity check	Satisfied / partial / unreported / contradicted

Rules:

• Claim-standard identity. The title, abstract, methods, and conclusion must name the same standard. If the title says one standard but the body applies a modified, weaker, narrower, or different standard, flag title/abstract overclaim. Grade Major or Fatal when the standard claim is central.
• Criterion-by-criterion satisfaction. "Framework fulfilled" is false or overstated if any required criterion is unreported, citation-borrowed without verification, only partially satisfied, or satisfied under a different standard. Grade by centrality.
• Current-paper vs citation-borrowed warrant. Separate "this paper directly showed X" from "this paper cites prior work for X." Citation-borrowed criteria must be citation-verified in Phase 4 before they can carry the framework claim.
• Local warrant boundary. A strong broader literature can support the scientific conclusion while leaving this paper's own framework/proof claim overstated. Do not let consensus or later corroboration repair the wording of the paper under review.
• Operational equivalence check. The operation actually performed must match the operation claimed. "Measured a proxy", "used a preparation", "analysed a convenience sample", or "applied a classifier" is not automatically equivalent to the claimed active agent, construct, population, or endpoint.

Active-Agent / Material Isolation Audit

Mandatory material question: what, in concrete terms, was actually used? If "purified X", "isolated Y", "treated W", "administered Z", "the dataset", "the intervention", or a named construct carries the conclusion, check whether the paper characterises it enough to support the active-agent or construct claim.

For any causal, mechanistic, intervention, infection, toxicology, material-science, ML, survey, or dataset claim, identify:

Dimension	Minimum question
Active agent / construct	What exact entity is claimed to do the work?
Carrier matrix	What else was administered, measured, exposed, cultured, processed, sampled, or bundled with it?
Preparation / processing	How was it produced, filtered, purified, extracted, passaged, cleaned, labelled, transformed, split, or normalised?
Dose / version / route	What amount, version, route, time window, population, or environment was used?
Exclusion controls	Were mock, sham, placebo, heat-inactivated, vehicle-only, blank, negative, contamination, carrier-only, confounder, leakage, or sensitivity controls used?
Identity verification	How was the active agent, sample, construct, dataset, endpoint, or label verified independently of the outcome?

If the claimed active agent is not separated from plausible co-administered causes, carrier effects, processing artefacts, contaminants, batch effects, dataset leakage, measurement artefacts, or construct drift, flag active-agent / construct under-determination. Grade as Major when the conclusion can be repaired by caveat or controls; Fatal when the central causal/proof claim depends on the unresolved identity.

Phase 3 — Statistical And Causal Sufficiency

Use specialist routing first:

• Route causal licence and evidence strength to scientific-fact-classification when the paper's conclusion depends on causation.
• Route hidden assumption stacks or named criteria to first-principles-thinking.
• Route rhetorical or theoretical overreach to fallacy-bias-and-manipulation-analysis.

Fallback minimum checks:

Risk	Check
p-hacking / forking paths	Pre-registration, number of tests, selective reporting, p-values clustered below threshold
Low power	A priori power, confidence intervals, Type-M/sign errors
Small n / responder skew	Per-group n, affected/unaffected counts, non-responder fraction, whether the central claim describes all subjects or only responders
Multiple comparisons	Correction or explicit exploratory framing
Wrong model/test	Distribution, dependence, clustering, unit of analysis
Practical irrelevance	Absolute effects, baseline risk, clinical/policy significance
Relative-only effect claim	Event counts, baseline risk, absolute effect, relative effect, timeframe, population
Odds / hazard / rate ratio as risk	Metric named exactly; conversion justified before risk language
Subgroup cherry-pick	Pre-specified subgroup, interaction test, all subgroups reported
Pseudoreplication	Unit of analysis equals unit of randomisation/sampling
ML leakage	Split integrity, contamination, repeated test-set tuning
Causal overreach	Design identifies causation, temporality, confounding, reverse causation, language calibration
Reverse causation unresolved	Directionality failure; downgrade causal language unless design or analysis rules out reverse direction

Quote the abstract/conclusion language and compare it with the design. "Associated with" in results becoming "causes" in the abstract is a Major or Fatal finding depending on centrality.

For any causal claim, state whether reverse causation was ruled out by design, tested directly, made implausible by mechanism/timing, or left unresolved. If reverse causation remains plausible, require association/prediction language. Grade Major or Fatal when a central conclusion, abstract claim, clinical/policy implication, or media-use hook depends on causal direction that the design cannot establish.

For animal, primate, clinical, intervention, challenge, toxicity, infection, or behavioural studies, always write the denominator sentence before grading: n=[total]; groups=[n per group]; affected/responded=[x/y per group]; unaffected/non-responded=[x/y per group]. If a headline, abstract, or conclusion implies a general effect while a substantial fraction of subjects were unaffected, flag responder-generalisation overreach. Grade Major or Fatal when the central claim depends on treating partial response as general effect.

For any comparative effect claim in epidemiology, clinical work, animal work, policy, safety, efficacy, behavioural outcomes, or model evaluation, write the effect decomposition before grading: counts/events by group, baseline/control risk, comparison/treatment risk, absolute risk difference, relative risk or named ratio, timeframe, population, and uncertainty. Keep ARR/ARI, RRR/relative increase, odds ratio, hazard ratio, and rate ratio separate. A relative-only benefit or harm claim is under-contextualised by default; grade Major when it carries the abstract, conclusion, clinical/policy implication, or media-use hook.

Phase 4 — Citation Verification

Verify the citations most able to change the recommendation:

• Citations supporting the central claim.
• Citations invoked to satisfy a named framework or criterion.
• Citations supporting methodological choices.
• Citations establishing novelty or gap.
• Citations supplying effect sizes, priors, or power assumptions.
• Citations to authoritative or contradicting prior literature.

If the paper's central claim relies on a cited empirical study, do not stop at "the citation says what the paper claims." Run a targeted cited-study peer review on that source: design, sample/materials, statistics, causal licence, reproduction/replication status, COI, and whether the cited study can bear the load assigned to it. This is mandatory for any cited study without which the reviewed paper's main conclusion, novelty claim, causal claim, or policy/clinical implication would materially weaken.

Recursion limit: one cited-study layer is mandatory when central. Follow a second layer only when the first cited study's own central warrant depends on another citation and that dependency could change the recommendation. Beyond two layers, stop and recommend a dedicated citation-chain review.

Process:

1. Fetch DOI, publisher page, preprint, PMC, repository, protocol, registry, or other primary source.
2. Locate the specific cited claim.
3. Compare paper's characterisation with source content.
4. Follow citation chains to the primary at least once for load-bearing claims.
5. For central empirical dependencies, perform the targeted cited-study peer review above.
6. Check retraction, expression of concern, PubPeer or equivalent where relevant.

Verdicts:

Verdict	Meaning
Supports	Cited source says what the paper claims.
Partial	Source supports a weaker or narrower claim.
Contradicts	Source points against the paper's claim.
Unrelated	Source does not bear on the claim.
Unverifiable	Source inaccessible, unpublished, "data not shown", personal communication, or otherwise not checkable.

Discrepancy template:

Cited as:             [paper's claim about the source, verbatim]
Source actually says: [quote or precise summary from fetched source]
Discrepancy type:     Supports-weaker | Partial-overlap | Contradicts | Unrelated | Misquotes | Wrong-direction | Retracted
Severity:             Fatal | Major | Minor
Warrant:              (traced — fetched [date]) | (memory — unverified, source unavailable)

Phase 5 — Literature Context And Deployment Gap

Audit both the paper's lane and its downstream use:

Question	Check
Is the paper consistent with recent systematic reviews/meta-analyses?	Fetch relevant synthesis if load-bearing
Are strong contradictions or replications engaged?	If not, flag selective context
Is novelty real?	Check whether similar methods/results already exist
Has the result been reproduced or independently replicated?	Prefer reproduction/replication over venue or citation status
Are downstream users citing it correctly?	Sample later papers, policy, regulatory, media, or institutional uses

Deployment-gap categories:

• Inside-lane — downstream use matches what the paper actually shows.
• Lane-stretched — downstream use is stronger than the paper supports.
• Outside-lane — downstream use makes the paper bear a claim it is silent on or contradicts.

If the paper is being used downstream as causal, clinical, regulatory, or policy authority while its own design cannot bear that load, flag the deployment gap separately from in-paper faults. If the paper itself encourages the overuse, grade accordingly.

When the literature itself is contested and source-counting may be laundered through one originator network, route to investigative-reasoning.

Phase 6 — Reproducibility, Transparency, And COI

Check:

Area	Minimum
Data	Public, controlled-access with clear process, or unavailable
Code	Available, versioned, executable enough to reproduce analyses
Methods	Protocol detail sufficient for reproduction and independent replication
Materials	Reagents, suppliers, catalogue numbers, corpus/data versions, survey instrument
Pre-registration	Present, followed, deviations declared
COI	Financial, institutional, ideological, author contribution, funder role
Openness limits	Paywalls, inaccessible supplements, unavailable data, undisclosed materials

Separate two checks:

• Reproduction: can the reported analyses/results be recovered from the same data, code, materials, and protocol?
• Replication: has an independent team, sample, lab, population, instrument, or dataset tested the same claim?

A prestigious peer-reviewed paper with unavailable data/code or unreproducible analyses is downgraded. A preprint or low-status venue with open materials and reproduced analyses can outrank a high-status paper on scientific warrant, though it may still need independent replication before strong generalisation.

Use osint-research for author/funder/retraction/affiliation checks when those facts become load-bearing.

Phase 7 — Severity And Recommendation

Severity:

Tag	Definition	Typical effect
Fatal	Central claim falsified, unsupported, or unevaluable	Reject or fundamental redesign
Major	Core claim overstated or method insufficient, fixable with substantial revision	Major revisions
Minor	Specific overclaim, check missing, caveat needed	Minor revisions
Optional	Useful improvement but not required	Suggestion
Praise	Genuine strength worth naming	Fairness and calibration

Recommendation: Accept / Minor / Major / Reject-resubmit / Reject.

State explicitly what would change the recommendation upward or downward.

Output

# Peer Review: [title]

## Summary
- **Paper:** [title, authors, venue/status, date]
- **Genre / field:**
- **Recommendation:** Accept / Minor / Major / Reject-resubmit / Reject
- **Verdict:** [one sentence]

## Paper Map
[research question, methods, results, conclusions, load-bearing claims, inference gap]

## What the Paper Does Well
[2-5 genuine strengths]

## Fatal Findings
[Each: quoted passage -> named fault -> why fatal -> fix if possible -> warrant]

## Major Findings
[Each: quoted passage -> named fault -> severity rationale -> required action -> warrant]

## Minor Findings

## Optional Suggestions

## Methodology Audit
[field-calibrated checks from Phase 2]

## Statistical And Causal Audit
[specialist outputs or fallback checks; quote specific numbers/language; state reverse-causation status for causal claims]

## Sample And Responder Denominators
| Group | n | Affected/responded | Unaffected/non-responded | Exclusions/missing | Claim language fits denominator? | Severity | Warrant |
|---|---|---|---|---|---|---|---|

## Quantified Effect Decomposition
| Claim | Population/timeframe | Events / total by group | Baseline risk | Comparison risk | Absolute effect | Relative effect / metric | Uncertainty | Practical meaning | Severity | Warrant |
|---|---|---|---|---|---|---|---|---|---|---|

## Citation Verification
| Paper claim | Cited source | Source actually says | Verdict | Severity | Warrant |
|---|---|---|---|---|---|

## Framework-To-Operation Traceability
| Framework / standard claim | Requirement | Directly shown in this paper | Citation-borrowed support | Material / dataset / intervention identity | Controls / exclusions | Status | Severity | Warrant |
|---|---|---|---|---|---|---|---|---|

## Active-Agent / Material Isolation
| Claim | Claimed active agent / construct | What was actually used | Carrier matrix / co-administered material | Preparation / processing | Identity verification | Exclusion controls | Adequate? | Severity | Warrant |
|---|---|---|---|---|---|---|---|---|---|

## Targeted Cited-Study Reviews
| Cited study | Why central | Method/statistical adequacy | Reproduction/replication status | Can bear cited load? | Severity impact | Warrant |
|---|---|---|---|---|---|---|

## Literature Context And Deployment Gap
| Downstream use / literature claim | What this paper actually supports | Inside-lane / Lane-stretched / Outside-lane | Warrant |
|---|---|---|---|

## Reproducibility, Transparency, And COI
[data/code/materials/protocol/COI/funder-role findings]

## Specialist Checks
[which skills were invoked or should be invoked, and what paper-level dependency they affect]

## Sources & Warrants
| Review finding / citation verdict | Source | URL | Access date | Publication date | Warrant | Funding / ownership / mandate / alignment |
|---|---|---|---|---|---|---|

## Confidence & Severity
- **Counts:** Fatal / Major / Minor / Optional / Praise
- **Confidence in this review:**

## What Would Change This
- Upward:
- Downward:

## Self-Audit
- **Symmetry test:** Would the same verdict be reached if the paper's conclusion ran the other way? Execute the flip; do not merely assert.
- **Standards applied:** [genre and field]
- **Difference in approach vs actual fault separated:**
- **Reviewer priors named:** [topic/authors/funder direction, if any]

## Limits
- Domain expertise required for:
- Sources not accessible:
- Citations unverifiable:
- Specialist review still needed:

Quick Reference

Pattern	Risk	Default move
Title names one standard, methods apply another	Claim-standard mismatch	Grade title/abstract overclaim; decompose both standards
Abstract causal, design observational	Causal overreach	Major/Fatal; calibrate language or redesign
Reverse causation not addressed	Directionality failure	Downgrade to association or require design/analysis that rules out reverse direction
Named framework invoked but requirements not checked	Framework laundering	Build criterion-to-operation table; verify each requirement
Framework criterion satisfied only by citations	Citation-borrowed warrant	Verify cited source and separate current-paper evidence from borrowed support
Cited source supports weaker claim	Citation overstatement	Quote both; grade by centrality
Central claim rests on cited study	Unreviewed dependency	Run targeted cited-study peer review
Input/material under-characterised	Active-agent or construct under-determination	Identify carrier matrix, preparation, identity checks, and exclusion controls; Major/Fatal if central
Claimed active agent bundled with carrier, culture, vehicle, batch, dataset, or proxy	Matrix/confound ambiguity	Require mock/vehicle/blank/carrier-only or equivalent controls
Broad literature supports conclusion but paper overstates its own proof	Local warrant boundary breach	Preserve conclusion context but grade this paper's claim separately
p < .05 without effect size/CI	Statistical opacity	Require effect sizes and uncertainty
Small sample carries central claim	Fragility / low power	State per-group n; downgrade unless effect is robust and replicated
Half or more subjects unaffected	Responder-generalisation overreach	Separate responder result from general claim; grade by centrality
Relative risk reduction without baseline	Relative-effect laundering	Report ARR/RRR and event rates separately
Odds/hazard/rate ratio described as risk	Metric substitution	Rename metric or justify conversion from data
Many tests, one headline result	Multiple-testing risk	Require correction or exploratory framing
Data/code "available on request"	Reproducibility weakness	Downgrade transparency
Sample scope narrower than conclusion	Generalisation overreach	Restrict conclusion
Downstream citation uses paper for stronger claim	Deployment gap	Separate paper fault from misuse
COI disclosure absent in stake-heavy field	Disclosure failure	Require disclosure and source-network check
Prestigious venue used as evidence	Status laundering	Ignore venue as warrant; inspect methods/reproduction
Reproducible preprint vs unreproducible journal article	Evidence beats venue	Weight reproducibility and replication higher