Performance of the ALOGPS 2.1 program for octanol-water partition coefficient prediction with organic chemicals on the Canadian Domestic Substances List
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The KOWWIN and ALOGPS octanol-water partition coefficient (K~ow~) estimation software programs were compared for their capacity to accurately predict log K~ow~ values of 1596 organic compounds on the publicly available Domestic Substances List (DSL) from Environment Canada for which experimental data is available. KOWWIN contained a significantly lower number and magnitude of prediction errors compared to ALOGPS, particularly at experimental log K~ow~ values <2. Substantial predictive differences were observed between the two programs for 9093 compounds not having experimental K~ow~ data on the Canadian DSL. Predictive differences of up to 40 log K~ow~ units were found between KOWWIN and ALOGPS, and in some cases, the discrepancies were sufficiently large that strongly opposing hydrophobicity classifications were obtained.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it