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Record W1589271161 · doi:10.1503/cmaj.151006

We deserve a government that respects scientific integrity

2015· editorial· en· W1589271161 on OpenAlexvenueno aff
Erin Russell

Bibliographic record

VenueCanadian Medical Association Journal · 2015
Typeeditorial
Languageen
FieldHealth Professions
TopicPublic Health Policies and Education
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Scientific integrityResearch integrityPublic administrationCensusPublic healthPublic relationsPolitical scienceMedicineEngineering ethicsEnvironmental healthEngineeringPopulationPathology

Abstract

fetched live from OpenAlex

Federal scientists contribute to the health and safety of Canadians by sharing their knowledge, research and expertise with the public and decision-makers — or so we hope. When the federal government abolished the mandatory long-form census in 2010, replacing it with the voluntary National

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)0.035
metaresearch head score (Gemma)0.170
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.981
Threshold uncertainty score0.187

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.170
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0060.005
Bibliometrics0.0040.004
Science and technology studies0.0120.016
Scholarly communication0.0270.013
Open science0.0090.004
Research integrity0.0620.089
Insufficient payload (model declined to judge)0.0090.009

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 head0.067
GPT teacher head0.428
Teacher spread0.361 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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