Proposal for a graded approach to disclosure of interests in accredited CME/CPD
Bibliographic record
Abstract
Disclosing conflicts of interest (COIs) is an important step in the management of COIs and is considered to be crucial to the trustworthiness of presenters. There are significant variations in disclosure procedures regarding the following:a. How COI is assessed in declaration forms (e.g. type of question, respondent awareness)b. Type of relationshipsc. Detailing of information to program committee membersThese variations in procedures have in effect led toa. Underreporting of COIb. Reducing the informational value of declared COI to participantsThus, it has been the aim of the authors to propose a basic formula for a minimum standard declaration of financial COI, with the potential to be applicable to all types of accredited continuing medical education (CME) as well as to all individuals (e.g. speakers, authors) involved in planning and conduct of CME activities. This approach should also serve as basis for more elaborate disclosures as well as strategies for management of conflict of interests adapted to the risk of bias.Furthermore, we also propose a basic set of items to be declared as nonfinancial interests.
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 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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".