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: Of 40 associations sampled at random from those eligible among 341 papers that each relate one NHANES variable to one health condition (eligible meaning, among other rules, that its full text was open and that NHANES August 2021 to August 2023 could build its exposure, outcome, and population), 14 (35%; exact 95% confidence interval 21% to 52%, which treats the associations as independent) replicated in that cycle, meaning their estimate there has the published sign and a Benjamini-Hochberg-corrected p below 0.05, with each analysis computed as its paper's was. Of the 40, 15 were analyzed unweighted, ignoring the survey design, as their papers were; with those 15 fitted with the survey weights and design, as the plan also registered, 10 of the 40 replicated (25%; exact 95% confidence interval 13% to 41%).
• Published.Published: At an unadjusted two-sided alpha of 0.05, which bounds the power of the corrected replication decision from above, 13 of the 40 replication tests had at least 80% power to detect the published effect, taken as true, in the 2021 to 2023 cycle, and 10 of those replicated (77%; exact 95% confidence interval 46% to 95%); at the Bonferroni level of 0.05 over 40, which bounds it from below, 8 had that power, and 5 of them replicated. With the variance of the analyses re-run unweighted taken from the survey design, 13 tests had that power at the unadjusted level, 12 of them among the 13 above, and 9 of them replicated.
• Published.Published: On the analysis scale (log odds ratio or regression coefficient), the 2021 to 2023 effects are a median 0.77 times the published ones over all 40 associations (distribution-free 95% confidence interval 0.32 to 1.05) and 0.91 times (0.32 to 1.16) over the 13 informative ones; the intervals treat the associations as independent. The median is 0.53 over the 15 analyses re-run unweighted and 0.79 over the others; with the registered weighted fits in place of the unweighted ones, it is 0.85 (0.35 to 1.08).

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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.

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.

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