Is Bone Mineral Composition Disrupted by Organochlorines in East Greenland Polar Bears ( <i>Ursus maritimus</i> )?
Bibliographic record
Abstract
We analyzed bone mineral density (BMD) in skulls of polar bears (Ursus maritimus) (n = 139) from East Greenland sampled during 1892-2002. Our primary goal was to detect possible changes in bone mineral content (osteopenia) due to elevated exposure to organochlorine [polychlorinated biphenyls (PCBs), dichlorodiphenyl trichloroethane (DDT) and its metabolites, chlordanes (CHLs), dieldrin, hexacyclohexanes, hexachlorobenzene] and polybrominated diphenyl ether (PBDE) compounds. To ensure that the BMD value in skull represented the mineral status of the skeletal system in general, we compared BMD values in femur and three lumbar vertebrae with skull in a subsample. We detected highly significant correlations between BMD in skull and femur (r = 0.99; p < 0.001; n = 13) and skull and vertebrae (r = 0.97; p < 0.001; n = 8). BMD in skulls sampled in the supposed pre-organochlorine/PBDE period (1892-1932) was significantly higher than that in skulls sampled in the supposed pollution period (1966-2002) for subadult females, subadult males, and adult males (all, p < 0.05) but not adult females (p = 0.94). We found a negative correlation between organochlorines and skull BMD for the sum of PCBs (SigmaPCB; p < 0.04) and SigmaCHL (p < 0.03) in subadults and for dieldrin (p < 0.002) and SigmaDDT (p < 0.02) in adult males; indications for SigmaPBDE in subadults were also found (p = 0.06). In conclusion, the strong correlative relationships suggest that disruption of the bone mineral composition in East Greenland polar bears may have been caused by organochlorine exposure.
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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 | 0.000 |
| 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".