Évaluation des pratiques professionnelles des médecins généralistes d’Aquitaine concernant le dépistage du cancer du sein par palpation mammaire chez les femmes entre 25 et 49 ans
Bibliographic record
Abstract
Introduction: breast cancer is the most common cancer among women. Although its role is debated in other countries, breast cancer screening through clinical breast examination is recommended annually in France, starting at age 25. General practitioners play a key role in prevention and screening efforts. The main objective of our study was to examine the practices and methods used by general practitioners in Aquitaine when performing breast examinations on their patients aged 25 to 49 years. Materials and Methods: we conducted a quantitative, descriptive, observational and multicenter study using anonymous, computerized questionnaires from November 2023 to March 2024. Results: we received 165 responses to the questionnaire, representing a response rate of 3.8%. Most participants (83%) perform breast palpation, though not always in accordance with current recommendations in France. The primary reason for performing the procedure is the patient's request (80%). Female doctors and those with additional training in gynecology tend to perform clinical breast examinations more frequently than their male counterparts and those without gynecological training. Conclusion: our study shows the interest of general practitioners in breast cancer screening through breast examination. However, recommendations may evolve in the coming years, as has already occurred in several developed countries, including Canada and the United States.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".