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Record W2753353163 · doi:10.1186/s12961-017-0235-3

Knowledge sharing in global health research – the impact, uptake and cost of open access to scholarly literature

2017· article· en· W2753353163 on OpenAlexaff
Elise Smith, Stefanie Haustein, Philippe Mongeon, Fei Shu, Valéry Ridde, Vincent Larivière

Bibliographic record

VenueHealth Research Policy and Systems · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicAcademic Publishing and Open Access
Canadian institutionsUniversité du Québec à MontréalMcGill UniversityUniversité de Montréal
Fundersnot available
KeywordsHealth services researchHealth administrationPublic healthHealth economicsHealth policyHealth informaticsMedicinePublic relationsBusinessKnowledge managementPolitical scienceComputer scienceNursing

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.095
metaresearch head score (Gemma)0.371
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication, Open science
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.501

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0950.371
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0140.024
Science and technology studies0.0020.006
Scholarly communication0.0190.019
Open science0.0030.013
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.806
GPT teacher head0.732
Teacher spread0.074 · 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 designObservational
DomainEvaluation
GenreEmpirical

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

Citations153
Published2017
Admission routes1
Has abstractyes

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