(Tables S1,2) Stable isotopes in muscle tissue of polar bears (Ursus maritimus) from various regions of the Arctic
Bibliographic record
Abstract
The relative contribution of regional contamination versus dietary differences to geographic variation in polar bear (Ursus maritimus) contaminant levels is unknown. Dietary variation between Alaska, Canada, East Greenland, and Svalbard subpopulations was assessed by muscle nitrogen and carbon stable isotope (d15N, d13C) and adipose fatty acid (FA) signatures relative to their main prey (ringed seals). Western and southern Hudson Bay signatures were characterized by depleted d15N and d13C, lower proportions of C20 and C22 monounsaturated FAs and higher proportions of C18 and longer chain polyunsaturated FAs. East Greenland and Svalbard signatures were reversed relative to Hudson Bay. Alaskan and Canadian Arctic signatures were intermediate. Between-subpopulation dietary differences predominated over interannual, seasonal, sex, or age variation. Among various brominated and chlorinated contaminants, diet signatures significantly explained variation in adipose levels of polybrominated diphenyl ether (PBDE) flame retardants (14-15%) and legacy PCBs (18-21%). However, dietary influence was contaminant class-specific, since only low or nonsignificant proportions of variation in organochlorine pesticide (e.g., chlordane) levels were explained by diet. Hudson Bay diet signatures were associated with lower PCB and PBDE levels, whereas East Greenland and Svalbard signatures were associated with higher levels. Understanding diet/food web factors is important to accurately interpret contaminant trends, particularly in a changing Arctic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.096 | 0.014 |
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".