Relationships Between Authorship Contributions and Authors' Industry Financial Ties Among Oncology Clinical Trials
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.
Bibliographic record
Abstract
PURPOSE To test the hypothesis that authors who play key scientific roles in oncology clinical trials, and who therefore have increased influence over the design, analysis, interpretation or reporting of trials, are more likely than those who do not play such roles to have financial ties to industry. METHODS Data were abstracted from all trials (n = 235) of drugs or biologic agents published in the Journal of Clinical Oncology between January 1, 2006 and June 30, 2007. Article-level data included sponsorship, age group (adult v pediatric), phase, single versus multicenter, country (United States v other), and number of authors. Author-level data (n = 2,927) included financial ties (eg, employment, consulting) and performance of key scientific roles (ie, conception/design, analysis/interpretation, or manuscript writing). Associations between performance of key roles and financial ties, adjusting for article-level covariates, were examined using generalized linear mixed models. Results One thousand eight hundred eighty-one authors (64%) reported performing at least one key role, and 842 authors (29%) reported at least one financial tie. Authors who reported performing a key role were more likely than other authors to report financial ties to industry (adjusted odds ratio [OR], 4.3; 99% CI, 3.0 to 6.0; P < .0001). The association was stronger among trials with, compared with those without, industry funding (OR, 5.0 [99% CI, 3.4 to 7.5] v OR, 2.5 [99% CI, 1.3 to 4.8]), but was present regardless of sponsorship. CONCLUSION Authors who perform key roles in the conception and design, analysis, and interpretation, or reporting of oncology clinical trials are more likely than authors who do not perform such roles to have financial ties to industry.
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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 arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchResearch integrity Domain: Incentives · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| gpt | MetaresearchResearch integrity Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.225 | 0.280 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.029 | 0.097 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it