Imagerie par susceptibilité magnétique appliquée aux seins
Bibliographic record
Abstract
Le manuscrit suivant porte sur le développement d’une méthodologie de cartographie de\nla susceptibilité magnétique. Cette méthodologie a été appliquée au niveau des seins à\ndes fins de détection de microcalcifications. Afin de valider ces algorithmes, un fantôme\nnumérique ainsi qu’un fantôme réel ont été créés. À l’aide de ces images, les paramètres\nmodifiables de notre méthodologie ont été ajustés. Par la suite, les problèmes reliés à\nl’imagerie du sein ont été explorés, tel la présence de gras ainsi que la proximité des\npoumons. Finalement, des images in vivo, acquises à 1.5 et 7.0 Tesla ont été analysées\npar notre méthodologie. Sur ces images 1.5T, nous avons réussi à observer la présence\nde microcalcifications. D’un autre côté, les images 7.0T nous ont permis de présenter un\nmeilleur contraste que les images standards de magnitude.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".