Field survey of Canadian background soils: Implications for a new mathematical gas chromatography–flame ionization detection approach for resolving false detections of petroleum hydrocarbons in clean soils
Bibliographic record
Abstract
The reference method for the Canada-wide standard (CWS) for petroleum hydrocarbons (PHCs) in soil provides laboratories with methods for generating accurate and reproducible soil analysis results. The CWS PHC tier 1 generic soil-quality guidelines apply to 4 carbon ranges/fractions: F1 (C6-C10), F2 (C10-C16), F3 (C16-C34), and F4 (>C34). The methods and guidelines were developed and validated for soils with approximately 5% total organic carbon (TOC). However, organic soils have much higher TOC levels because of biogenic organic compounds (BOCs) originating from sources such as plant waxes and fatty acids. Coextracted BOCs can have elevated F2-F4 concentrations, which can cause false exceedances of PHC soil guidelines. The present study evaluated false PHC detections in soil samples collected from 34 background sites. The list of analytes included soil type, TOC, polycyclic aromatic hydrocarbons (PAHs), F2, F3, F4, F3a (C16-C22), and F3b (C22-C34). Soils with 3% to 41% TOC falsely exceeded the CWS PHC 300 mg/kg F3 coarse soil guideline. It was previously demonstrated that clean peat had F2:F3b ratios of less than 0.10, while crude oil spiked peat and spiked sand had higher ratios of greater than 0.10. In the present background study, all of the clean organic soils with at least 300 mg/kg F3 had F2:F3b ratios of less than 0.10, which indicated false guideline exceedances. Clean inorganic soils had low F3 concentrations, resulting in high F2:F3b ratios of greater than 0.10. Validation field studies are required to determine if the F2:F3b 0.10 PHC presence versus absence threshold value is applicable to crude oil- and diesel-contaminated sites.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".