Caractérisation des panaches industriels par imagerie hyperspectrale aéroportée
Bibliographic record
Abstract
La caractérisation des aérosols et des gaz produits par l'homme est un enjeu majeur pour la société car ces composants ont un impact direct sur la santé et le climat. Plusieurs techniques de caractérisation existent mais la télédétection aéroportée est une réponse potentiellement adaptée pour l'étude de ces sources si l'on veut avoir accès à leur expansion spatiale. De plus, l'imagerie hyperspectrale concernant tout le domaine optique, elle permet de couvrir l'ensemble des besoins nécessaires à la détection et la caractérisation des aérosols et des gaz. Après avoir introduit les motivations de l'étude des panaches industriels, un bref rappel est fait sur le principe de l'imagerie hyperspectrale. Ensuite, sont détaillées les méthodes de caractérisation des aérosols puis des gaz anthropiques à partir de cette technique et les informations physiques que l'on peut en extraire.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".