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Record W2046336223 · doi:10.1093/eurheartj/ehr464

Conflict of interest policies and disclosure requirements among European Society of Cardiology National Cardiovascular Journals

2012· article· en· W2046336223 on OpenAlexaff
Fernándo Alfonso, Adam Timmis, Fausto J. Pinto, Giuseppe Ambrosio, Hugo Ector, Piotr Kułakowski, Panos Vardas, Loizos Antoniades, Mansoor Ahmad, Eduard Apetrei, Kaduo Arai, Jean‐Yves Artigou, Michael Aschermann, Michael Böhm, Leonardo Bolognese, Raffaele Bugiardini, Ariel Cohen, István Édes, John Elias, Javier Galeano, Eduardo Guarda, Habib Haouala, M. Heras, Christer Höglund, Kurt Huber, I Hulín, Mario Ivanuša, R. Krittayaphong, Cheng‐Tai Kuo, C.-P. Lau, V. A. Lyusov, Germanas Marinskis, Manlio F. Márquez, Luíz Felipe Pinho Moreira, Alexander Mrochek, Р. Г. Оганов, Dimitar Raev, Mamanti Rogava, Olaf Rødevand, Vedat Sansoy, Hiroaki Shimokawa, Valentin Shumakov, Carlos Tajer, Ernst E. van der Wall, Christodoulos Stefanadis, Jørgen Videbæk, Thomas F. Lüscher

Bibliographic record

VenueEuropean Heart Journal · 2012
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsCanadian Journal of Communication (Canada)
Fundersnot available
KeywordsCredibilityTransparency (behavior)Conflict of interestMedicineAccountingPublic relationsCardiologyLawPolitical scienceBusiness

Abstract

fetched live from OpenAlex

Disclosure of potential conflicts of interest (COIs) is used by biomedical journals to guarantee credibility and transparency of the scientific process. Conflict of interest disclosure, however, is not systematically nor consistently dealt with by journals. Recent joint editorial efforts paved the way towards the implementation of uniform vehicles for COI disclosure. This paper provides a comprehensive editorial perspective on classical COI-related issues. New insights into the current COI policies and practices among European Society of Cardiology National Cardiovascular Journals, as derived from a cross-sectional survey using a standardized questionnaire, are discussed.

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)0.213
metaresearch head score (Gemma)0.450
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.994
Threshold uncertainty score0.971

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2130.450
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0050.004
Scholarly communication0.0080.005
Open science0.0030.004
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0050.002

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 head0.771
GPT teacher head0.567
Teacher spread0.203 · 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 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

Citations63
Published2012
Admission routes1
Has abstractyes

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