Identification of unresolved complex mixtures (<scp>UCMs</scp>) of hydrocarbons in commercial fish oil supplements
Bibliographic record
Abstract
BACKGROUND: Heightened awareness of the health benefits of fish oil consumption has led to a great increase in the number of fish oil supplements available to the consumer. Therefore manufacturers are continually looking for ways to distinguish their products from those of competitors. Minimally refined or virgin fish oils provide a unique feature; however, petroleum hydrocarbon contamination from oil spills is a reality in the world's oceans. The question arises whether oil produced from fish species caught in these polluted areas is free of petroleum hydrocarbons, with particular interest in unresolved complex mixtures (UCMs). This study investigates the presence of UCMs in commercially available fish oil supplements advertised as being virgin, as well as refined. RESULTS: Weathered petroleum hydrocarbons in the form of a UCM were found at 523 µg g(-1) in a virgin Alaskan salmon oil supplement. Supplements that were refined were free of this contamination. CONCLUSION: Fish used in the production of fish oil supplements appear to have accumulated petrogenic hydrocarbons in their tissues which were not removed by minimal oil refining. Further study is required to determine if there are any health implications associated with long-term consumption of these contaminated supplements.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".