Les leviers d’action pour un mix énergétique propre et sûr au service de la transition énergétique dans les territoires
Bibliographic record
Abstract
Les territoires multiplient leurs efforts pour atteindre les objectifs de la loi de transition énergétique pour la croissance verte, parmi lesquels figure la nécessité de porter la part des énergies renouvelables à 32 % de la consommation finale brute d’énergie en 2030. Cet article vise à recenser les risques industriels et environnementaux liés à l’émergence à la fois de nouveaux acteurs impliqués dans le déploiement des énergies renouvelables et de nouveaux matériaux et technologies. Associées à ces risques, des solutions techniques et organisationnelles sont proposées pour les maîtriser et tenter de faire de la transition une opportunité pour les territoires.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| 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".