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Record W4234179374 · doi:10.1136/bmj.331.7518.672

Academic medicine scenarios: final votes

2005· article· en· W4234179374 on OpenAlexfundno aff

Bibliographic record

VenueBMJ · 2005
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsnot available
FundersAgency for Healthcare Research and QualityMcMaster University
KeywordsComputer scienceData scienceAcademic medicineMedicineMedical education

Abstract

fetched live from OpenAlex

reduce urinary antimicrobial use even if a significant reduction in culture rate could not be shown.One limitation of our study is that the results may not be generalisable to nursing homes with fewer than 100 residents.Our study was underpowered to assess important differences in admissions to hospital and death between study arms.Another limitation is that differences between the study arms in antimicrobials courses for urinary indications were reduced during the final months of the study, although the trend was not statistically significant.This may have been due to fatigue of the healthcare provider with the intervention.We thank the staff of the study nursing homes and Holly Colwell for her assistance with the Idaho facilities.

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)0.033
metaresearch head score (Gemma)0.130
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.058
Threshold uncertainty score0.193

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.130
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0090.004
Scholarly communication0.0130.006
Open science0.0040.006
Research integrity0.0290.015
Insufficient payload (model declined to judge)0.0580.012

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 head0.270
GPT teacher head0.516
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2005
Admission routes1
Has abstractno

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