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Record W2104599417 · doi:10.1503/cmaj.1060108

The problem of evidence-based medicine in developing countries

2006· letter· en· W2104599417 on OpenAlexvenueno aff
A. A. Sabri

Bibliographic record

VenueCanadian Medical Association Journal · 2006
Typeletter
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsnot available
Fundersnot available
KeywordsMedical prescriptionAlternative medicineDeveloping countryComputer scienceCore (optical fiber)MedicineData sciencePharmacologyPathologyEconomic growth

Abstract

fetched live from OpenAlex

In a recent article, Caleb Alexander and associates[1][1] elucidate the issue of prioritizing and stopping prescription medicines, pointing to a lack of data on the safety and optimal means of discontinuing drugs.[1][1] This may be the core problem in developed countries, but the situation is

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)0.145
metaresearch head score (Gemma)0.402
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.855
Threshold uncertainty score0.765

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1450.402
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0050.008
Science and technology studies0.0070.029
Scholarly communication0.0160.025
Open science0.0060.014
Research integrity0.0680.094
Insufficient payload (model declined to judge)0.0080.003

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 head0.279
GPT teacher head0.387
Teacher spread0.109 · 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
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

Citations13
Published2006
Admission routes1
Has abstractyes

Explore more

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