Occurrence and characterisation of naphthenic acid fraction components in oil residues and sediments stranded on the shoreline of Chedabucto Bay, Nova Scotia, Canada
Bibliographic record
Abstract
Abstract In June 2016, oil residues and sediment samples were collected from the shoreline of Chedabucto Bay, Nova Scotia, Canada, at sites affected by the 1970 Arrow oil spill. This study aimed to investigate the occurrence, fate, and behaviour of oil components 45 years post-spill by analysing polar naphthenic acid fraction components (NAFCs) through high-performance liquid chromatography–high-resolution mass spectrometry (HPLC–HRMS). In all samples, the most abundant NAFC species were those having only oxygen as the heteroatom (Oo species, o indicating the number of oxygen atoms, from 1 to 8) and a high degree of saturation. NAFC species only containing two oxygen atoms (O2) accounted for 50–70% of all Oo species. The abundance of all remaining species was negligible compared with Oo species. NAFCs in most Arrow oil residues had higher levels of oxygen species than the oil remaining stored in the sunken tanker. Environmental sediment samples collected from near a marina away from the spill site contained a dominant biological, whereas all Arrow oil residues were mainly composed of NAFCs that are characteristic of petroleum. The abundance of NAFCs in the Arrow oil residues varied between sites, confirming that site-specific environmental conditions play a major role in controlling the fate and behaviour of oil components, including NAFCs.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".