Ecological indicators and source diagnostic ratios of aliphatic and polyaromatic hydrocarbons in marine sediments of Qatar
Bibliographic record
Abstract
The marine ecosystems surrounding oil and gas production sites are particularly vulnerable to ecological harm that may be affected by its operations. In this study, we examined the composition, contaminant sources, and the potential ecological risk of aliphatic hydrocarbons (AH) and polyaromatic hydrocarbons (PAH) in the marine sediments along the western coast of Qatar. The ΣAHs concentration ranged from <0.10 to 246 ng⋅g−1 (site SD2) while the ΣPAH concentration ranged from <0.10 to 44 ng⋅g−1 (site SD10). Pollution concentration profile was site specific where AH and PAH concentrations were relatively higher within close proximity to the oil and gas production. TOC appeared to be positively correlated with PAH and therefore a good indicator for PAH but not for AH. Low molecular weight even-carbon numbered alkanes (n-C10-18) were more abundant than the higher molecular weight (n-C20-34) AHs. The Σ16PAHs compositional analysis mean concentrations were composed of 2-ring (6%), 3-ring (18%), 4-ring (48%), 5-ring (28%), and 6-ring (0.14%), respectively. Fluoranthene obtained the highest concentration of 11 ng⋅g−1 (site SD10). Diagnostic ratios and hydrocarbon parameters suggested mixed sources of petrogenic, pyrolytic, and biomass except for vehicular traffic. The overall results for AH and PAH indicated low pollution based on pollution criteria and were below the threshold limit set by the National Oceanic and Atmospheric Administration (NOAA) and the Canadian Sediment Quality Guidelines (CSQG). This suggests low probability of a negative toxic effect caused by these contaminants however, continuous long term-monitoring is needed to ensure these pollutants do not exceed the current levels.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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 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".