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<i>Advanced statistics:</i> Understanding Medical Record Review (MRR) Studies

2004· article· en· W2119470638 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAcademic Emergency Medicine · 2004
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsMcMaster UniversityHamilton Health Sciences
Fundersnot available
KeywordsMedicineStrengths and weaknessesMedical literatureMEDLINEData sciencePathology

Abstract

fetched live from OpenAlex

Medical record review (MRR) studies have been reported to make up 25% of all scientific studies published in emergency medical (EM) journals. However, unlike other study designs, there are no standards for reporting MRRs and very little literature on the methodology for conducting them. The purpose of this article is to provide the reader with methodological guidance regarding the strengths and weaknesses of these types of studies.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.126
metaresearch head score (Gemma)0.259
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.371
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1260.259
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0030.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0670.003

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 head0.876
GPT teacher head0.630
Teacher spread0.246 · 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