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Record W2004899111 · doi:10.1503/cmaj.060637

Editorial policy: industry funding and editorial independence

2006· editorial· en· W2004899111 on OpenAlexvenueno aff
Nancy MacDonald

Bibliographic record

VenueCanadian Medical Association Journal · 2006
Typeeditorial
Languageen
FieldArts and Humanities
TopicAcademic Writing and Publishing
Canadian institutionsnot available
Fundersnot available
KeywordsIndependence (probability theory)Computer science

Abstract

fetched live from OpenAlex

The separation of editorial decisions from financial issues is essential to ensure editorial independence. Given this, it is important to reflect upon current policy and practices with respect to advertising and supplement sponsorship. Consider, first, advertising. CMA policy is clear: Editorial

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)0.091
metaresearch head score (Gemma)0.339
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.989
Threshold uncertainty score0.479

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0910.339
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0060.006
Science and technology studies0.0110.007
Scholarly communication0.0310.010
Open science0.0060.003
Research integrity0.0440.031
Insufficient payload (model declined to judge)0.0990.155

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 head0.009
GPT teacher head0.241
Teacher spread0.232 · 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
DomainIncentives
GenreEditorial

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

Citations4
Published2006
Admission routes1
Has abstractyes

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