Effects of inbreeding on reproductive success in endangered North Atlantic right whales
Bibliographic record
Abstract
) remain. With extremely low levels of genetic diversity, limited options for mates, and variation in reproductive success across females, there is concern regarding the potential for genetic limitations of population growth from inbreeding depression. In this study, we quantified reproductive success of female North Atlantic right whales with a modified de-lifing approach using reproductive history information collected over decades of field observations. We used double-digest restriction site-associated sequencing to sequence approximately 2% of the genome of 105 female North Atlantic right whales and combined genomic inbreeding estimates with individual fecundity values to assess evidence of inbreeding depression. Inbreeding depression could not explain the variance in reproductive success of females, however we present evidence that inbreeding depression may be affecting the viability of inbred fetuses-potentially lowering the reproductive success of the species as a whole. Combined, these results allay some concerns that genetic factors are impacting species survival as genetic diversity is being retained through selection against inbred fetuses. While still far fewer calves are being born each year than expected, the small role of genetics underlying variance in female fecundity suggests that variance may be explained by external factors that can potentially be mitigated through protection measures designed to reduce serious injury and mortality from human activities.
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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 | 0.000 | 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".