L'impatto del settore della refrigerazione sui cambiamenti climatici.
Bibliographic record
Abstract
Le secteur du froid, conditionnement d’air, pompes a chaleur et cryogenie compris, represente 7,8 % des emissions globales de gaz a effet de serre (sur la base d’estimations de l’IIF pour l’annee 2014). Parmi ces emissions, 37 % sont des emissions directes de CFC, HCFC et HFC et 63 % des emissions indirectes dues a la production et au transport de l’energie utilisee par les systemes de froid (emissions de CO2 principalement). L’Amendement de Kigali au protocole de Montreal, adopte en octobre 2016, prevu pour diminuer progressivement la production et la consommation de HFC, devrait permettre d’eviter une hausse des temperatures moyennes entre 0, 1 °C et 0,3 °C d’ici 2100. Le secteur du froid etant amene a croitre fortement dans les decennies a venir, l’IIF propose une serie de recommandations pour que cette croissance soit durable, avec un impact limite sur le changement climatique. Ce document est une traduction du Resume pour les decideurs de la 35e Note d'information sur les technologies du froid.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".