Environmentally Responsible Product Assessments for the Automobiles Made in China
Bibliographic record
Abstract
This article discusses a general assessment of how the environmental performance of the automobile has changed over the years. We performed an SLCA and used the AT&T matrix and Delphi-technique to compare a 1990s era automobile(made in china) to one from the 2000s of China. From the comparison, we calculated 5 life stages of automobile production include premanufacturing, product manufacture, product delivery, product use and recycling. The comparison shows moderate environmental stewardship during resource extraction, packaging. The ratings during manufacturing and refurbishment/ recycling/ disposal are both poor, and during customer use are abysmal though it have some improvement. The overall rating of 1990s is far below what might be desired. In contrast, the overall rating for the 2000s vehicle is much better than that of the earlier vehicle but still leaving plenty of room for improvement. Key words: AT&T matrix, environment, LCA, SLCA, automobile Resume: Cet article entreprend une evaluation generale du fait que comment la performance environnementale de l’automobile a change ces dernieres annees. Nous avons effectue un SLCA et utilise la matrice de l’AT&T ainsi que le technique Delphi afin de comparer un automobile des annees 1990 (fabrique en Chine) avec un autre des annees 2000. A travers la comparaison, nous avons calcule 5 etapes de la production de l’automobile : prefabrication, fabricarion du produit, livraison du produit, utilisation du produit, recyclage. La comparaison montre un management environnemental modere pendant l’extraction et l’empaquetage des ressources. Les evaluations durant la fabrication et la reconstruction /recyclage/ elimination sont toutes miserables, et pendant la periode d’utilisation par les clients elle apparait epouvantable malgre des ameliorations. L’evaluation generale des annees 90 est loin de repondre a notre desir. Au contraire, celle des annees 2000 est bien meilleure que la precedente, mais reste beaucoup a desirer. Mots-Cles: matrice de l’AT&T, environnement, LCA, SLCA, automobile
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".