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Record W3098080120 · doi:10.1136/bmjebm-2020-111503

Ten years later: a review of the US 2009 institute of medicine report on conflicts of interest and solutions for further reform

2020· review· en· W3098080120 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBMJ evidence-based medicine · 2020
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsConflict of interestGuidelineAlternative medicinePolitical scienceHealth careMedical researchPublic relationsMedical educationEngineering ethicsMedicineEngineeringLaw

Abstract

fetched live from OpenAlex

Conflicts of interest (COIs) in healthcare are increasingly discussed in the literature, yet these relationships continue to influence healthcare. Research has consistently shown that financial COIs shape prescribing practices, medical education and guideline recommendations. In 2009, the Institute of Medicine (IOM, now the National Academy of Medicine) published Conflicts of Interest in Medical Research, Practice, and Education —one of the most comprehensive reviews of empirical research on COIs in medicine. Ten years after publication of theIOM’s report, we review the current state of COIs within medicine. We also provide specific recommendations for enhancing scientific integrity in medical research, practice, education and editorial practices.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearchResearch integrity
Domain: Incentives · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
gptMetaresearchResearch integrity
Domain: Methods · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.667
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.774
GPT teacher head0.617
Teacher spread0.156 · 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