Forensic source attribution for toluene in environmental samples
Bibliographic record
Abstract
The formation of toluene by microbiological processes can confound environmental investigations relating to petroleum releases. This is because toluene is a constituent of petroleum and can move readily within wetland environments, and analysis for toluene in relation to a petroleum release can lead to incorrect assignment of detected biogenic toluene as related to the release. No legally defensible method of distinguishing biogenic and petrogenic origins of detectible concentrations of toluene have been demonstrated to date. Using example petrogenic samples and samples of peat from 2 wetland environments, a poor bog and a poor fen, the present study demonstrates the use of an established ASTM International analytical methodology that was originally designed for arson analysis for the determination of the origin of toluene. Environmental forensic data-interpretation methods such as chromatogram inspection and diagnostic ratios are shown to be capable of readily distinguishing biogenic and petrogenic origins of toluene. Environ Toxicol Chem 2018;37:729-737. © 2017 SETAC.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.136 | 0.057 |
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".