Polycyclic Aromatic Hydrocarbons in Soil of the Canadian River Floodplain in Oklahoma
Bibliographic record
Abstract
The accumulation of polycyclic aromatic hydrocarbons (PAH) in soil, plants, and water may impart negative effects on ecosystem and human health. We quantified the concentration and distribution of 41 PAH (n = 32), organic C, total N, and S (n = 140) and investigated PAH sources using a chronosequence of floodplain soils under a natural vegetation succession. Soil samples were collected between 0- and 260-cm depth in bare land (the control), wetland, forest, and grassland areas near a closed municipal landfill and an active asphalt plant (the contaminant sources) in the north bank of the Canadian River near Norman, OK. Principal component, cluster, and correlation analyses were used to investigate the spatial distribution of PAH, in combination with diagnostic ratios to distinguish pyrogenic vs. petrogenic PAH suites. Total PAH concentration (SigmaPAH) had a mean of 1300 ng g(-1), minimum of 16 ng g(-1), and maximum of 12,000 ng g(-1). At 0- to 20-cm depth, SigmaPAH was 3500 +/- 1600 ng g(-1) (mean +/- 1 SE) near the contaminant sources. The most common compounds were nonalkylated, high molecular weight PAH of pyrogenic origin, i.e., fluoranthene (17%), pyrene (14%), phenanthrene (9%), benzo(b)fluoranthene (7%), chrysene (6%), and benzo(a)anthracene (5%). SigmaPAH in the control (130 +/- 23 ng g(-1)) was comparable to reported concentrations for the rural Great Plains. Perylene had a unique distribution pattern suggesting biological inputs. The main PAH contamination mechanisms were likely atmospheric deposition due to asphalt production at the 0- to 20-cm depth and past landfill operations at deeper depths.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".