The mating system of polar bears: a genetic approach
Bibliographic record
Abstract
Parentage analysis data for 583 individuals genotyped at 27 microsatellite loci were used to study the mating system of polar bears ( Ursus maritimus Phipps, 1774) in the Barents Sea area. We discriminated statistically between full and half-siblings identified through only one common parent. We document for the first time multiple paternity in polar bears. We demonstrated for both sexes low fidelity to mating partners over time. We did not detect any significant difference between the age distribution of adult males at capture and the age distribution of males siring cubs. This might indicate that the male’s age and size are less indicative of the reproductive success than previously thought. This is further supported by a rather long mean litter interval of 3.9 years for males siring several litters. The mating system of polar bears in the Barents Sea appears to be promiscuous, usually with a single successful father siring full siblings within a year, but with consecutive litters of a mother being fathered by different males. We discuss how population density, landscape characteristics, and adult sex ratio might influence the mating system of polar bears. This is of particular importance for management decisions such as, e.g., implementing sex ratios in hunting quotas.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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".