INDICATORS FOR THE ENVIRONMENTAL IMPACT OF WASTE EMISSIONS: COMPARISON OF EXERGY AND OTHER INDICATORS
Bibliographic record
Abstract
Exergy is compared with other indicators for the environmental impact of waste emissions in an effort to better understand its potential as, or as the basis for, an effective indicator of the potential of an emitted substance to impact the environment. Relations between environmental impact and exergy in general and chemical exergy of waste emissions in particular are observed to support the use of exergy as such an indicator. The measure of disequilibrium with respect to a reference environment provided by exergy is considered, along with the consequence that the exergy of unrestricted waste emissions has the potential to impact the environment. Exergy is observed to exhibit many characteristics of other indicators of environmental impact, which are mainly empirical in nature. An exergy-based indicator could contribute to the development of rational and objective procedures for assessing the harmful effects on the environment of a substance and predicting its potential for environmental impact. The potential usefulness of exergy in addressing environmental problems is concluded to be significant, but further research is needed to develop objective exergy-based indicators that are practical for the potential of a substance to impact on the environment.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".