Bibliographic record
Abstract
This article presents findings and recommendations of an international conference held in Cairo, Egypt in 2003 concerning issues of ethical practice in how information is provided to and by medical practitioners. Professional advertising to practitioners and the public is necessary, but should exclude misrepresentation of qualifications, resources, and authorship of research papers. Medical institutions are responsible for how staff members present themselves, and their institutions. Medical associations, both governmental licensing authorities and voluntary societies, have powers and responsibilities to monitor professional advertisement to defend the public interest against deception. Medical journals bear duties to ensure authenticity of authorship and integrity in published papers, and the scientific basis of commercial advertisers' claims. A mounting concern is authors' conflict of interest. Mass newsmedia must ensure accuracy and proportionality in reporting scientific developments, and product manufacturers must observe truth in advertising, particularly in Direct-to-Consumer advertising. Consumer protection by government agencies is a continuing responsibility.
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 | 0.043 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.052 |
| Scholarly communication | 0.018 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.014 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".