QSARs for aquatic toxicity: celebrating, extending and displaying the pioneering contributions of Ferguson, Konemann and Veith
Bibliographic record
Abstract
Significant advances were made in the development of quantitative structure-activity relationships (QSARs) relating molecular structure to aquatic toxicity by three studies over 30 years ago by Ferguson in 1939, Konemann in 1981, and Veith and colleagues in 1983. We revisit the original concepts and data from these studies and review these contributions from the bases of current perspectives on the hypothesized mechanism of baseline narcotic toxicity and the underlying thermodynamic and kinetic aspects. The relationships between LC50, octanol-water partition coefficient, aqueous solubility, chemical activity and chemical volume fraction in lipid phases are outlined including kinetic influences on measured toxicities. These relationships provide a compelling and plausible explanation of the success of these and other QSARs for aquatic toxicity. Suggestions are made for further advances in these QSARs to improve assessments of toxicity by baseline narcotic toxicity and selective modes of action, especially using emerging quantum chemical computational capabilities.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".