Genetic identifications challenge our assumptions of physical development and mother–calf associations and separation times: a case study of the North Atlantic right whale (Eubalaena glacialis)
Bibliographic record
Abstract
Abstract While photo-identification is an effective tool to monitor individuals in wild populations, it has limitations. Specifically, it cannot be applied to very young animals before their identifying features have stabilized or to dead, decomposed animals. These shortfalls leave gaps in our understanding of survival, parentage, age structure, physical development, and behavioral variability. Here we report on 13 case studies of North Atlantic right whale, Eubalaena glacialis , calves that required genetics to track their life history data. These case studies revealed unexpected variations in mother–calf associations and separation times, as well as calf physical development. Prior to this study, calves were assumed to have died if their mothers were always alone on the feeding ground in the calf’s birth year. Using genetics and photo-identification, four such calves were discovered to be alive; two of the four possibly weaned earlier than expected at 7.5–8.0 months. To put these early separations in context, photo-identification data were queried and revealed that mothers and calves are seen apart from each other on the feeding grounds in 10–40% of all spring/summer sightings; previously, there were no published data on how often pairs are seen apart in the calf’s birth year. Two dead whales initially logged as calves of the year were discovered to be juveniles, thus allowing skewed survival estimates for calves of the year to be corrected. Genetically sampling animals early in their lives before they disperse or separate from their mothers provides an important means of individual identification at a time when photo-identification is not reliable.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".