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Record W6964998276 · doi:10.3205/23ebm131

RoB2 – das aktualisierte Risk-of-Bias-Tool für RCTs von Cochrane

2023· article· de· W6964998276 on OpenAlexaff

Bibliographic record

VenueGerman Medical Science (German Research Foundation) · 2023
Typearticle
Languagede
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsCochrane
Fundersnot available
KeywordsRandomized controlled trialMEDLINECochrane collaborationClinical trial

Abstract

fetched live from OpenAlex

Beschreibung: Das Cochrane Risk-of-Bias-Tool ist ein etabliertes Instrument zur Einschätzung des Bias-Risikos in randomisierten kontrollierten Studien. Vor einigen Jahren wurde eine aktualisierte Fassung entwickelt und in das aktuelle Cochrane-Handbuch für systematische Übersichtsarbeiten [zum vollständigen Text gelangen Sie über die oben angegebene URL]

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)0.236
metaresearch head score (Gemma)0.546
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.764
Threshold uncertainty score0.942

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2360.546
Meta-epidemiology (narrow)0.0060.004
Meta-epidemiology (broad)0.0160.042
Bibliometrics0.0240.010
Science and technology studies0.0010.003
Scholarly communication0.0090.006
Open science0.0050.008
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0350.004

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 head0.629
GPT teacher head0.629
Teacher spread0.000 · 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
DomainMethods
GenreMethods

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

Citations0
Published2023
Admission routes1
Has abstractyes

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