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Record W3179613356 · doi:10.1126/science.373.6552.268

European law could boost clinical trials reporting

2021· article· en· W3179613356 on OpenAlexaff
Barbara Casassus

Bibliographic record

VenueScience · 2021
Typearticle
Languageen
FieldMedicine
TopicScience, Research, and Medicine
Canadian institutionsWorld Federation of Science Journalists
Fundersnot available
KeywordsEnforcementBusinessLaw enforcementAccountingPolitical scienceLaw

Abstract

fetched live from OpenAlex

New database and stricter enforcement could help end lapses in reporting results.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.421
metaresearch head score (Gemma)0.682
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.579
Threshold uncertainty score0.714

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4210.682
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.006
Bibliometrics0.0070.007
Science and technology studies0.0040.008
Scholarly communication0.0260.023
Open science0.0070.011
Research integrity0.0360.033
Insufficient payload (model declined to judge)0.0270.010

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.595
GPT teacher head0.621
Teacher spread0.026 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainReporting
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2021
Admission routes1
Has abstractyes

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