Identification de gaz traces à court et à long temps de vie atmosphérique à partir de mesures du sondeur IASI/Metop-A
Bibliographic record
Abstract
Ces dernières années, des progrès majeurs ont été accomplis pour mesurer les gaz traces absorbants faiblement dans l’atmosphère, à partir d’observations spatiales à haute résolution spectrale. Dans ce travail, nous appliquons la transformation dite de blanchiment sur les spectres de radiance enregistrés par IASI (Interféromètre Atmosphérique de Sondage Infrarouge) à bord des plateformes satellites Metop, et montrons qu’elle permet de se débarrasser de la majeure partie du signal de fond contenu dans les spectres, mettant en évidence les anomalies spectrales. Celles-ci peuvent par la suite être attribuées à des changements dans l’abondance atmosphérique de gaz traces. Ceci est illustré pour deux cas distincts :(1) un panache de feux australiens de 2019/2020, conduisant à l’identification non ambiguë de neuf signatures rares de composés organiques ;(2) des spectres observés sur 10 années d’intervalle, à partir desquels les changements dans huit substances halogénées à long temps de vie sont identifiés.
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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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".