Adaptation of Fugacity Models To Treat Speciating Chemicals with Constant Species Concentration Ratios
Bibliographic record
Abstract
A "multiplier" method is developed by which multimedia mass balance fugacity models designed to describe the fate of a single chemical species can be applied to chemicals that exist as several interconverting species. The method is applicable only when observed ratios of species concentrations in each phase are relatively constant and there is thus no need to define interspecies conversion rates. It involves the compilation of conventional transformation and intermedia transport rate expressions for a single, selected key species, and then a multiplier, Ri, is deduced for each of the other species. The total rate applicable to all species is calculated as the product of the rate for the single key species and a combined multiplier (1 + R2 + R3 + etc.). The theory is developed and illustrated by two examples. Limitations of the method are discussed, especially under conditions when conversion rates are uncertain. The advantage of this approach is that existing fugacity and concentration-based models that describe the fate of single-species chemicals can be readily adapted to estimate the fate of multispecies substances such as mercury which display relatively constant species proportions in each medium.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".