Temporal Trends of Persistent Organic Pollutants in Barents Sea Polar Bears (<i>Ursus maritimus</i>) in Relation to Changes in Feeding Habits and Body Condition
Bibliographic record
Abstract
Temporal trends of persistent organic pollutants (POPs: PCBs, OH-PCBs, p, p′ -DDE, HCB, β-HCH, oxychlordane, BDE-47, and 153) in relation to changes in feeding habits and body condition in adult female polar bears ( Ursus maritimus ) from the Barents Sea subpopulation were examined over 20 years (1997–2017). All 306 samples were collected in the spring (April). Both stable isotope values of nitrogen (δ 15 N) and carbon (δ 13 C) from red blood cells declined over time, with a steeper trend for δ 13 C between 2012 and 2017, indicating a decreasing intake of marine and high trophic level prey items. Body condition, based on morphometric measurements, had a nonsignificant decreasing tendency between 1997 and 2005, and increased significantly between 2005 and 2017. Plasma concentrations of BDE-153 and β-HCH did not significantly change over time, whereas concentrations of Σ 4 PCB, Σ 5 OH-PCB, BDE-47, and oxychlordane declined linearly. Concentrations of p, p′ -DDE and HCB, however, declined until 2012 and 2009, respectively, and increased thereafter. Changes in feeding habits and body condition did not significantly affect POP trends. The study indicates that changes in diet and body condition were not the primary driver of POPs in polar bears, but were controlled in large part by primary and/or secondary emissions of POPs.
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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) | 0.001 | 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".