Ž.The Science of the Total Environment 287 2002 4559 Persistent organochlorine pollutants in ringed seals and polar bears collected from northern Alaska
Bibliographic record
Abstract
Ž. Ž.Blubber samples from ringed seal Phoca hispida; n8 and polar bear subcutaneous fat Ursus maritimus; n5 were collected near Barrow, Alaska in 1996 as part of the Alaska Marine Mammal Tissue Archival Project Ž.AMMTAP and retained in the National Biomonitoring Specimen Bank at the National Institute of Standards and Ž.Technology in Gaithersburg, Maryland USA. The samples were analyzed for a variety of persistent organochlorine Ž. Ž. Ž.pollutants POPs including polychlorinated biphenyls PCBs, hexachlorocyclohexanes HCHs, chlordane and Ž.metabolites, hexachlorobenzene HCB and DDTs and metabolites. The geometric mean, on a wet mass basis, of Ž. Ž.PCBs sum of 29 congeners and congener groups were 732282 ngg 1 S.D. in seals and 33951442 ngg in Ž. Ž.polar bears. The geometric mean of DDTs, HCHs -, - and - HCH and HCB concentrations wet mass basis in seals and bears were 562261 ngg vs. 74.839 ngg, 380213 ngg vs. 515 ngg, and 17.410.1 ngg vs. Ž183153 ngg, respectively. The geometric mean sum of chlordane chlordane, sum of cis- and trans-chlordane,.cis- and trans-nonachlor, oxychlordane and heptachlor epoxide and dieldrin concentrations in ringed seals and polar bears were 753617 ngg vs. 720315 ngg and 38.622.8 ngg vs. 13065 ngg, respectively. Apparent Ž.bioaccumulation factors polar bearringed seal POP concentrations were lower in the animals sampled near Barrow, Alaska than in those from locations in the Canadian Arctic. This suggests that polar bears are also preying Disclaimer: Certain commercial equipment or instruments are identified in the paper to specify adequately the experimental
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".