Enantiomer-Specific Accumulation of PCB Atropisomers in the Bowhead Whale (<i>Balaena mysticetus</i>)
Bibliographic record
Abstract
Blubber (n = 40) and liver (n = 20) samples from the bowhead whale (Balaena mysticetus) were collected during the 1997-1998 Native (Inuit) subsistence harvests in Barrow, AK. Bowhead tissues and zooplankton were analyzed for polychlorinated biphenyl (PCB) concentrations and the enantiomeric fractions (EFs) of eight chiral PCB congeners (PCB-91, 95, 135, 136, 149, 174, 176, and 183) to quantify the enantiomer-specific accumulation of PCBs in this cetacean. PCB concentrations in bowhead blubber were low (mean +/- 1 SE: 610 +/- 54 ng g(-1) lipid) relative to other cetaceans. The accumulation of several chiral PCBs (PCB-91, 135, 149, 174, 176, and 183) in bowhead blubber was enantiomer-specific relative to bowhead liver and zooplankton, suggesting that biotransformation processes within the bowhead whale are enantioselective. The EFs for PCB-95 and 149 were significantly correlated with body length in male and female whales, while EFs for PCB-91 correlated with length in males only. Despite evidence for enantioselective biotransformation, all three congeners bioaccumulated in the bowhead relative to PCB-153. Results suggest that enantioselective accumulation of PCB-91, 95, and 149 is influenced by PCB concentrations, age, and/or the modification of an uncharacterized stereoselective process (or processes) during sexual maturity.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".