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Record W7095897308

Letter from the Editor

2016· article· en· W7095897308 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicMedical Research and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsPublishingLetter to the editorMedical journalJournal editorMEDLINE
DOInot available

Abstract

fetched live from OpenAlex

No longer free for all Since the Canadian Medical Association Journal wentonline in the mid-1990s, the Canadian Medical Asso-ciation has provided unrestricted access to all CMAJ content. However, given the changing economic times, we can no longer afford to do so. As of January 2010, some content will be restricted to CMA members, subscribers and pay-per-view readers. This was a difficult decision, because we believe that scien-tific information should be accessible to all. The CMA, our edi-torial team and many past editors of CMAJ have strongly endorsed open access. Online, CMAJ is publishing more content, with new arti-cles posted weekly and news pieces added almost daily.1 However, we have experienced a perfect storm involving rising editorial costs to handle the extra content, and dra-matic decreases in advertising. Processes such as peer

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)0.002
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.977
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0030.004
Open science0.0020.001
Research integrity0.0180.018
Insufficient payload (model declined to judge)0.0230.015

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 head0.171
GPT teacher head0.540
Teacher spread0.369 · 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
Domainnot available
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

Citations0
Published2016
Admission routes1
Has abstractyes

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