Bibliographic record
Abstract
BACKGROUND: Honorary and ghost authorship, as well as competing interests, are well documented concerns related to the publication of scientific articles. Guidelines for writing and publishing scientific manuscripts are available, including those of the International Committee of Medical Journal Editors (ICMJE). OBJECTIVES: The primary objective of this descriptive cross-sectional study was to identify, in the instructions for authors of pharmacy practice journals, guidance on authorship and competing interests. The secondary objective was to suggest suitable corrective measures for more transparent authorship. METHODS: The first step of the project was to identify journals in the area of pharmacy practice. The instructions for authors of each journal were then reviewed to determine recommendations for avoiding problems related to authorship and competing interests. Finally, the members of the research team formulated potential corrective measures for researchers. RESULTS: Of 232 pharmacy journals identified, 33 were deemed to focus on pharmacy practice. A total of 24 (73%) of these journals mentioned that they followed ICMJE policies, 14 (42%) asked authors to complete a competing interests disclosure form at the time of submission, 17 (52%) had a formal definition of authorship, and 5 (15%) asked for details of each author's contribution. A list of 40 criteria was developed to define authorship status. CONCLUSION: Fewer than half of the journals asked authors to provide a competing interests disclosure form upon submission of an article, and only half had a formal definition of authorship. The scientific publication of papers relevant to pharmacy practice is not free from issues related to publication transparency. Publishing articles online and using a checklist to detail each author's contribution may help to limit the associated risks. [Publisher's translation].
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 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 | 0.003 | 0.025 |
| 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 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.850 | 0.661 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".