D<sub>ow</sub>and K<sub>aw,eff</sub>vs. K<sub>ow</sub>and K°<sub>aw</sub>: Acid/base ionization effects on partitioning properties and screening commercial chemicals for long-range transport and bioaccumulation potential
Bibliographic record
Abstract
A set of 543 ionizable commercial organic compounds with various acid/base functionalities and experimental octanol-water partitioning coefficients (log Kow) were obtained from the Canadian Domestic Substances List. Corresponding pH-dependent octanol-water distribution coefficients (log Dow) and air-water partitioning coefficients (log Kaw,eff) were estimated using the SPARC software program, as were log Kow and log Kaw degrees values for the neutral forms of each chemical. Significant ionization dependent effects on chemical screening results at various pH values were obtained using established criteria for bioaccumulation potential (BAP) in aquatic organisms, terrestrial animals, and humans, as well as for atmospheric long range transport potential (LRTP). Future modelling efforts for environmental and toxicological screening of commercial chemicals should therefore explicitly include the influence of ionization for both weak and strong organic acids and bases on bioavailability and air-water mobility within the respective regulatory frameworks. Functional group specific sorption of both ionizable and neutral compounds to particulate and dissolved inorganic and organic matter will also affect chemical screening results for BAP and LRTP. More complex sorption related modelling in various types of representative aquatic systems also appears necessary to achieve reliable chemical screening results for commercial organic compounds.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".