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Record W2071434978 · doi:10.1136/bmj.326.7385.397

Unit of analysis errors should be clarified in meta-analyses

2003· letter· en· W2071434978 on OpenAlexaff
Ruth Thomas

Bibliographic record

VenueBMJ · 2003
Typeletter
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsCochraneUniversity of Ottawa
Fundersnot available
KeywordsMeta-analysisUnit (ring theory)Cluster (spacecraft)Non-sampling errorComputer sciencePsychologyMedicineInternal medicineAlgorithmMathematics education

Abstract

fetched live from OpenAlex

EDITOR—Weingarten et al present a comprehensive study in what is a complex area of research.1 We were, however, unclear whether any of the included primary studies had unit of analysis errors and how the authors dealt with such studies in their meta-analysis. Unit of analysis errors occur in cluster randomised trials when individual patients' data …

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)0.251
metaresearch head score (Gemma)0.742
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.749
Threshold uncertainty score0.923

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2510.742
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0070.007
Bibliometrics0.0050.007
Science and technology studies0.0030.008
Scholarly communication0.0060.012
Open science0.0080.003
Research integrity0.0360.053
Insufficient payload (model declined to judge)0.0050.005

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 head0.952
GPT teacher head0.629
Teacher spread0.323 · 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
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

Citations16
Published2003
Admission routes1
Has abstractyes

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Same venueBMJSame topicMeta-analysis and systematic reviewsFrench-language works237,207