Estimates of Octanol–Water Partitioning for Thousands of Dissolved Organic Species in Oil Sands Process-Affected Water
Bibliographic record
Abstract
In this study, the octanol-water distribution ratios (DOW, that is, apparent KOW at pH 8.4) of 2114 organic species in oil sands process-affected water were estimated by partitioning to polydimethylsiloxane (PDMS) coated stir bars and analysis by ultrahigh resolution orbitrap mass spectrometry in electrospray positive ((+)) and negative ((-)) ionization modes. At equilibrium, the majority of species in OSPW showed negligible partitioning to PDMS (i.e., DOW <1), however estimated DOW's for some species ranged up to 100,000. Most organic acids detected in ESI- had negligible partitioning, although some naphthenic acids (O2(-) species) had estimated DOW ranging up to 100. Polar neutral and basic compounds detected in ESI+ generally partitioned to PDMS to a greater extent than organic acids. Among these species, DOW was greatest among 3 groups: up to 1000 for mono-oxygenated species (O(+) species), up to 127,000 for NO(+) species, and up to 203,000 for SO(+) species. A positive relationship was observed between DOW and carbon number, and a negative relationship was observed with the number of double bonds (or rings). The results highlight that nonacidic compounds in OSPW are generally more hydrophobic than naphthenic acids and that some may be highly bioaccumulative and contribute to toxicity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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 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".