P236 Documentation Of Intellectual Conflicts Of Interests Proved Critical In A Clinical Practice Guideline
Bibliographic record
Abstract
Background The American College of Chest Physicians (ACCP) Antithrombotic Guidelines (AT9) addressed both financial and intellectual COI, and restricted panellists from voting on recommendations on which they declared a primary conflict. The extent to which intellectual COI restricted participation beyond financial COI is uncertain. Objective The objective is to describe financial and intellectual COI among AT9 panellists and assess their overlap. Methods The AT9 executive committee developed definitions and categorizations of primary and secondary financial and intellectual COI. panellists reported, for each recommendation, their financial and intellectual COIs. We analysed their declarations. Results Among 102 panellists, the average number of recommendations for which panellist declared COI was: 2.1 (SD 5.7) for secondary financial COI, 1.7 (SD 3.5) for primary financial COI, 5.0 (SD 9.9) for secondary intellectual COI, and 2.5 (SD 5.0) for primary intellectual COI. Of the 102 panellists 37 (36%) declared a primary intellectual but no primary financial COI for at least one recommendation. Among 431 recommendations, the average number of panellists per recommendation who declared COI was: 0.5 (SD 0.8) for secondary financial COI, 0.4 (SD 0.9) for primary financial COI, 1.2 (SD 1.2) for secondary intellectual COI, and 0.6 (SD 1.2) for primary intellectual COI. In 63 recommendations (23%) at least one panellist had a primary intellectual COI but no primary financial COI Conclusion A substantial number of declarations resulted in restrictions based on intellectual COI in the absence of financial COI.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.043 | 0.306 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.014 | 0.007 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".