MétaCan
Menu
Back to cohort
Record W2206201175 · doi:10.1136/bmj.h4601

Liberating the data from clinical trials

2015· editorial· en· W2206201175 on OpenAlexafffund
David Henry, Tiffany Fitzpatrick

Bibliographic record

VenueBMJ · 2015
Typeeditorial
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsInstitute for Clinical Evaluative SciencesUniversity of Toronto
FundersEconomic and Social Research CouncilMedical Research CouncilCanadian Institutes of Health Research
KeywordsHarmClinical trialPsychologyIntensive care medicineMedicineData scienceComputer scienceSocial psychologyInternal medicine

Abstract

fetched live from OpenAlex

Liberated trial data have enduring potential to benefit patients, prevent harm, and correct misleading research

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)0.086
metaresearch head score (Gemma)0.345
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Open science
Consensus categoriesnone
DomainCandidate signal: Reproducibility · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.991
Threshold uncertainty score0.453

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0860.345
Meta-epidemiology (narrow)0.0070.004
Meta-epidemiology (broad)0.0110.009
Bibliometrics0.0070.005
Science and technology studies0.0060.013
Scholarly communication0.0210.012
Open science0.0090.004
Research integrity0.0550.084
Insufficient payload (model declined to judge)0.0110.013

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 head0.942
GPT teacher head0.780
Teacher spread0.163 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
DomainReproducibility
GenreEditorial

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

Citations23
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueBMJSame topicEthics in Clinical ResearchFrench-language works237,207