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Record W2467284210 · doi:10.7895/ijadr.v5i1.233

Addiction journals and the management of conflicts of interest

2016· article· en· W2467284210 on OpenAlexvenueno aff
Kerstin Stenius

Bibliographic record

VenueThe International Journal of Alcohol and Drug Research · 2016
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsAddictionPoliticsQuality (philosophy)PsychologyConflict of interestPolitical sciencePublic relationsEpistemologyLawPsychiatryPhilosophy

Abstract

fetched live from OpenAlex

Stenius, K. (2016). Addiction journals and the management of conflicts of interest. The International Journal Of Alcohol And Drug Research, 5(1), 9-10. doi:http://dx.doi.org/10.7895/ijadr.v5i1.233Scientific journals are crucial for a critical and open exchange of new research findings and as guardians of the quality of science. Today, as policy makers increasingly justify decision-making with references to scientific evidence, and research articles form the basis for evidence for specific measures, journals also have an indirect responsibility for how political decisions will be shaped.

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)0.215
metaresearch head score (Gemma)0.720
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.968

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2150.720
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0080.010
Science and technology studies0.0060.007
Scholarly communication0.0210.010
Open science0.0050.013
Research integrity0.0110.015
Insufficient payload (model declined to judge)0.0380.011

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 head0.718
GPT teacher head0.631
Teacher spread0.087 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
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

Citations3
Published2016
Admission routes1
Has abstractyes

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