Simulation numérique de l'opération de pièges microfluidiques à échantillons
Bibliographic record
Abstract
REMERCIEMENTSJe tiens remercier mon directeur de recherche, Thomas Gervais, pour ses conseils, son support, ses ides et son accueil dans son groupe de recherche.Son expertise en modlisation a t indispensable pour toutes les tapes de ma matrise.Il m'a appris toujours considrer l'applicabilit des rsultats de simulations.En me poussant collaborer et communiquer avec des exprimentateurs, il a permis au projet de rester concret et pertinent.Je tiens aussi souligner la collaboration essentielle de Mlina Astolfi, tudiante diplme la matrise, une bonne partie de mon projet.Ses rflexions et ses questions sur les effets hydrodynamiques et de diffusion-convection m'ont permis de pousser mes connaissances et de concentrer mes efforts sur les aspects essentiels de ces effets.De plus, la collaboration avec Mohana Marimuthu, tudiante post-doctorante du groupe, a permis de concentrer la rflexion par rapport aux effets capillaires.Ses questions sur les principes de fonctionnement du dispositif qu'elle a invent (SIMMS chip) ont t la source de la majeure partie des sections sur la formation de gouttelettes et sur le remplissage de dispositifs microfluidiques.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".