The Tenuous Use of Exergy as a Measure of Resource Value or Waste Impact
Bibliographic record
Abstract
Exergy is a thermodynamic concept that has been widely promoted for assessing and improving sustainability, notably in the characterization of resources and wastes. Despite having many notable benefits, exergy is often misused by authors who tend to apply it as an intrinsic characteristic of an object (i.e., as a static thermodynamic variable). Using both theoretical and empirical evidence the authors present five key limitations that must be overcome before exergy can be applied to characterize objects: (1) the incompatibility between exergy quality and resource quality; (2) the inability of exergy to characterize non work-producing resources via the concentration exergy; (3) the constraints placed on the derivation of exergy; (4) problems with the exergy reference environment; and (5) the multiple perspectives applied to exergy analysis. Until the limitations are addressed, exergy should only be used for its original purpose as a decision making tool for engineering systems analysis.
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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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.020 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".