Réponse makers à la pandémie de la COVID-19 : le cas des respirateurs open source
Bibliographic record
Abstract
Durant la pandémie de la COVID-19, les makers se sont mobilisés réduire les risques de pénurie d'objets nécessaires au personnel soignant. Ont notamment été développés des respirateurs dits open source. Ce matériel médical complexe exige cependant des procédures de validation avant toute utilisation sur un patient en détresse respiratoire. À côté des respirateurs complets, nous avons pu identifier d'autres types de projets visant, soit à hacker du matériel existant, soit à fabriquer des pièces en rupture de stock. Nous avons mis à jour des mécanismes de coordination entre makers et autres parties prenantes indispensables à la maturité des projets. Nous avons dégagé des modalités de mises à disposition différentes allant de la diffusion restreinte de projets développés de manière agile à la mise en accès libre de véritables communs informationnels. L'accessibilité des connaissances acquises ouvre de nouvelles opportunités en matière de production locale low-cost.
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 | 0.029 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.019 | 0.006 |
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".