Response for Key Learnings and Perspectives of a Newly Implemented Sex-and Gender-Based Medicine Modular Course Integrated into the First-Year Medical School Curriculum: A Mixed-Method Survey [Response to Letter]
Bibliographic record
Abstract
Nicola Luigi Bragazzi,1–4 Hicham Khabbache,5 Khalid Ouazizi,6 Driss Ait Ali,6 Hanane El Ghouat,6 Laila El Alami,6 Hisham Atwan,7 Ruba Tuma,8–10 Nomy Dickman,10 Raymond Farah,10,11 Rola Khamisy-Farah9,10 1Human Nutrition Unit (HNU), Department of Food and Drugs University of Parma, Parma, Italy; 2Laboratory for Industrial and Applied Mathematics (LIAM), Department of Mathematics and Statistics, York University, Toronto, ON, Canada; 3Postgraduate School of Public Health, Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy; 4United Nations Educational, Scientific and Cultural Organization (UNESCO) Chair, Health Anthropology Biosphere and Healing Systems, University of Genoa, Genoa, Italy; 5Director of the UNESCO Chair “Lifelong Learning Observatory” (UNESCO/UMSBA), Fez, Morocco; 6Department of Psychology, Faculty of Arts and Human Sciences Fès-Saïss, Sidi Mohamed Ben Abdellah University, Fez, Morocco; 7Department of Internal Medicine, Kaplan Medical Centre, Hebrew University, Rehovot, Israel; 8Department of Obstetrics and Gynecology, Galilee Medical Center, Nahariya, Galilee, Israel; 9Clalit Health Services, Akko, Israel; 10Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel; 11Department of Internal Medicine B, Ziv Medical Center, Safed, IsraelCorrespondence: Nicola Luigi Bragazzi, Human Nutrition Unit (HNU), Department of Food and Drugs University of Parma, Via Volturno 39, Parma, 43125, Italy, Tel +39 0521 903121, Email nicolaluigi.bragazzi@unipr.it
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".