Éditorial
Bibliographic record
Abstract
Noëlle Lasne es una médica de cabecera. Después de haber trabajado en un consultorio de la ciudad, se incorporó a la misión francesa de Médicos Sin Fronteras en 1990, cuya creación representó un importante punto de inflexión en las actividades de la ONG humanitaria internacional. Se trataba de un retorno «a casa» motivado por el creciente número de situaciones de no acceso a la atención, ya fuera para los extranjeros indocumentados, los trabajadores/as sin prestación por desempleo o las víctimas de nuevas formas de precariedad. Coordinó este trabajo a lo largo de la década de 1990, cuando la labor de atención sanitaria de la misión estuvo en contacto directo con las iniciativas y movilizaciones que desembocaron en la creación de la Cobertura Sanitaria Universal y la Asistencia Médica Estatal para los extranjeros indocumentados. Recuerda esta experiencia para Mouvements.
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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.077 | 0.032 |
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".