A Comprehensive and Critical Compilation, Evaluation, and Selection of Physical–Chemical Property Data for Selected Polychlorinated Biphenyls
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
Accurate physical–chemical properties (aqueous solubility SW, octanol–water partition coefficient KOW, vapor pressure P, Henry’s law constant H, octanol–air partition coefficient KOA, octanol solubility SO) are of fundamental importance for modeling the transport and fate of organic pollutants in the environment. Energies of phase transfer are used to describe the temperature dependence of these properties. When trying to quantify the behavior of contaminant mixtures such as the polychlorinated biphenyls, consistent physical–chemical properties are required for each individual congener. A complete set of temperature dependent property data for sixteen polychlorinated biphenyls (PCB-3, 8, 15, 28, 29, 31, 52, 61, 101, 105, 118, 138, 153, 155, 180, 194) was derived, based on all experimentally obtained values reported for these congeners in the literature. Log mean values derived from the experimental data were adjusted to yield an internally consistent set of data for each congener. These adjusted data also show a greater degree of interhomologue consistency, which can be illustrated with the help of simple quantitative structure-property relationships that use molar mass and the number of chlorine substitutions in ortho-positions as descriptors. The extent of the required adjustment gives an indication of the uncertainty of the averaged measured values and is typically lower than might be expected from the range of the reported measured values.
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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