Every study, searchable

Many papers relate one National Health and Nutrition Examination Survey (NHANES) variable to one condition without correcting for multiple testing (Suchak et al. (2025)). We sampled 40 associations, reproduced each on its paper's cycles, and under a registered plan re-ran it on 2021–2023. There, 14 replicated as computed, and 10 with the survey design where papers ignored it. Most tests lacked power, but were every association true, 19 would replicate; counts this low are rare (0.047, or 0.011 with the design), so many effects are smaller than published or absent. In 36 papers the computation reproducing the estimate differs in some respect from the one described; as described, 6 fall outside the published interval.

• Published.Published: Re-implemented from each paper and the public files on the cycles it analyzed, 39 of the 40 published estimates meet the registered reproduction criterion, our estimate inside the published 95% confidence interval, with a median ratio of our estimate to the published one of 0.99 (95% confidence interval 0.92 to 1.01); the criterion shows a computation consistent with the published numbers, not the authors' own. The one that does not meet it modeled the absence of its outcome while reporting the odds of its presence: coded as stated it gives 1.41, and reversed 0.71, against a published 0.71.
• Published.Published: Two independent codings of how each of the 102 recorded departures bearing on a headline estimate is established (by the paper itself, by recomputation that identifies another computation, or unresolved), made by two agents of one model family from the recorded details rather than from the papers, agreed on 98 (Cohen's kappa 0.91); as settled, 23 are shown by the paper itself, 72 by recomputation, and 7 are unresolved. Of 20 of these departures drawn at random, an agent of the same model family that recorded none of them, reading each paper's full text for what the record says of the paper (not what recomputation gives), found 18 describing their paper correctly, 2 misstating something about it though the departure stands, and 0 misdescribing it so that the departure does not stand (exact 95% upper bound for that share 17%); records misstating anything are 10% of those checked (1% to 32%), and the others were not checked.
• Published.Published: On the cycles each paper analyzed, the analysis as the paper describes it, with the recorded departures bearing on the headline that are computations (coding, sample, weighting, or model) and that our code follows put back as its text describes them, under rules carried in code/described_rules.md, changes the specification of 32 of the 40 analyses; 3 departures could not be built from the public files and stay as followed. Among those 32, the described estimate is a median 0.99 times the followed one on the analysis scale, within 1% of it for 6, falls outside the published 95% confidence interval for 5, and lacks a significant estimate (p below 0.05) with the published sign for 13, against 6 as followed. Counting the paper whose followed version already codes its outcome as stated, 6 of the 40 analyses as described fall outside the published interval.

12 more claims

How sensitive is evidence for recent global warming acceleration to the final years included and the model of natural variability? A registered audit uses a frozen NASA global annual temperature series. A fixed-breakpoint model estimates a warming-rate increase of 0.232 °C per decade, with a confidence interval from 0.106 to 0.358. A search over possible breakpoints gives p = 0.0271 with fitted autocorrelation, but p = 0.4078 when the recent endpoint years are excluded. Stronger assumed autocorrelation also weakens the test. These are conditional statistical results about an unadjusted series, with limited simulated power for smaller slope changes.

• Published, Reproduced, Reviewed.Published, Reproduced, Reviewed: In the frozen NASA GISTEMP annual series for 1970-2025, a fixed-2015-knot model estimates a warming-rate increase of 0.232 degrees Celsius per decade with a 95% HAC interval of 0.106 to 0.358, while the registered breakpoint-search p-value is 0.0271 through 2025, 0.4078 through 2022, and 0.1726 through 2025 when the AR(1) lag coefficient is fixed at 0.6.

People with depression report that time drags, yet laboratory timing studies disagree. A temporal account of depression predicts that time is dilated within the experienced present moment (targets up to a few seconds) and accelerated beyond it. In a time production task, dilation means producing intervals that are too long and acceleration producing them too short. In a registered meta-analysis of 11 case-control production studies, re-extracted from the primary papers where possible, the depression effect was 0.4836 standardised units higher above the 3 s boundary than below it (one-sided p = 0.03380082115675086), with overproduction at short targets (g = -0.2851) and underproduction at longer ones (g = 0.1985), neither significant alone. The effect rose by 0.6302 per tenfold increase in duration. Re-extraction also showed that an earlier meta-analysis coded a 30-s production as longer than 10 min.

• Published, Reviewed.Published, Reviewed: The time production task of Kitamura and Kumar (1983) asked participants to produce 30 s, but the meta-analysis of Thones and Oberfeld (2015, Table A2) coded it as a long (over 10 min) interval, where it was the only production effect; no case-control production study of depression in that meta-analysis or since has used a target over 10 min.
• Published, Reproduced, Reviewed.Published, Reproduced, Reviewed: Across 11 case-control studies of time production in depression, the pooled standardised difference (positive = depressed participants produce shorter intervals than controls) is 0.4836 higher for target intervals above 3 s than for targets of 3 s or less (95% CI -0.0431 to 1.0103; one-sided p = 0.034), with pooled g = -0.2851 at 3 s or less (3 studies; 95% CI -0.6917 to 0.1214) and g = 0.1985 above 3 s (10 studies; 95% CI -0.1378 to 0.5348).
• Published, Reproduced, Reviewed.Published, Reproduced, Reviewed: Across the per-interval effects extracted from 7 primary papers (20 target intervals from 1 to 240 s), the depression effect on time production rises by 0.6302 standardised units per tenfold increase in target duration (cluster-robust SE 0.2128; one-sided p = 0.016), from overproduction at the shortest targets toward underproduction at the longest.

Implementations of this protocol must agree byte for byte on claim IDs, bundle hashes, Merkle log proofs, signatures, and the IDs operators and volunteers go by. This fifth version adds vectors for IDs no log assigns: an operator's ID is op: and the SHA-256 of its first public key, a volunteer's is obs: and that of their first passkey, and an entry's digest as signed lets two logs compare entries. The log's example leaves now name their operator by ID. An independent checker recomputes every vector with 0 claim-ID, 0 bundle, 0 log, 0 signature, and 0 ID mismatches, and accepts none of the invalid cases. Hashing Python's json.dumps output still gets 3 of 20 claim IDs wrong.

• Published, Reproduced, Reviewed.Published, Reproduced, Reviewed: Hashing Python's json.dumps output with sorted keys and compact separators gives wrong claim IDs for claims files in which Python wrote numbers such as 1.0, 1e-05, or 1e+16, because RFC 8785 formats numbers as ECMAScript does; formatting numbers that way gives the listed ID for every vector.
• Published, Reproduced, Reviewed.Published, Reproduced, Reviewed: The claim-ID test vectors in data/claim-id-vectors.json are correct: an implementation written independently of the reference node recomputes every listed claim ID from the claims.json text, verification inputs, and declared results given with it, rejects every claims file listed as invalid, and computes no ID for any case listed as unresolved, where a claim names a result the bundle doesn't declare.
• Published, Reproduced, Reviewed.Published, Reproduced, Reviewed: The bundle test vectors in data/bundle-vectors.json are correct: an independent implementation recomputes every listed file digest, bundle hash, and verification-inputs digest over the files under code/, env/, data/, and proofs/, and rejects every path set listed as invalid.

3 more claims

How often do stars like the Sun release superflares of $10^{34}$ erg or more? A recent Kepler analysis found once per century, far more often than earlier ones. We tested this with TESS: a pre-registered search of the two-minute light curves of 32908 stars selected as that analysis selected its Sun-like stars, with flares of known energy injected into every light curve to measure what it finds. It counted 78 superflares where the once-per-century rate predicts 23.4: 3.33 times that rate (interval 2.63 to 4.15), one per 33 years per star, far above the earlier rates. Every planned subset and sensitivity analysis gives a ratio above one. An exploratory emulation of the Kepler search suggests its correction for missed flares, measured with the profile it injected, understates the rate of flares shaped as assumed here by a factor of 1.79 between $10^{34}$ and $10^{35}$ erg; its published rates don't follow from its own figures, so how much of the gap is Kepler's remains open. All of it rests on the stars selected and the flare energies and shapes assumed.

• Published.Published: Searching again, with the same seeds, the 254 audited light curves (every one with a vetted event of 10^34 erg or more on the stars not set aside as fast rotators, and 150 others chosen by the hash of their names) reproduces every column of their rows of the search's tables, 243,234 fields, within a relative 1e-6, except template-fit parameters of candidates that fail vetting, which differ across platforms by at most 1%; and selecting the sample again from the catalogs gives the same 39,937 confirmatory stars and 121,190 light curves.
• Published.Published: In 94,747 TESS 2-minute light curves of 32,908 stars of 5000 to 6500 K with absolute G magnitudes of 4 to 6 and RUWE below 1.4 (5,605 star-years), the pre-registered search, with its SAP test corrected after registration to require the uncorrected flux to rise, counted 78 flares of bolometric energy 10^34 erg or more where the rate Vasilyev et al. (2024) measured with Kepler predicts 23.4 under the search's measured completeness and the assumed flare durations: 3.33 times that rate (95% CI 2.63 to 4.15), about once per 33 years per star; the registered code counted 79 (3.37 times, 2.67 to 4.20).
• Published.Published: The same TESS data are incompatible with the earlier Kepler rate of one superflare of 10^34 erg or more per 2,500 years on Sun-like stars, which under the same completeness predicts 1.04 counted flares where 78 were found (Poisson probability below 10^-100).

5 more claims