How compromised is reproductive performance in the endangered North Atlantic right whale?
Bibliographic record
Abstract
The endangered North Atlantic right whale Eubalaena glacialis showed limited recovery from the cessation of industrial whaling until 2011, and has since been in decline. Research is therefore focused on identifying what factors are limiting recovery and what conservation actions will be most effective. A compromised reproductive rate is one of the reasons for this lack of recovery, yet there is no consensus on how to quantify reproductive performance. As one potential solution, we propose a relatively simple approach where we calculate the theoretical maximum number of calves each year. Comparing this expected number to those observed (which is thought to be an accurate representation of those births that actually occurred) provides a means to quantify the degree to which reproduction is compromised annually and trends thereof over time. Implementing this approach shows that, between 1990 and 2017, the number of calves born never came close to the theoretical maximum, resulting in overall reproductive performance of only about 27% of that expected. In addition to quantifying the degree to which reproduction is compromised, this approach should also be useful for quantifying the role of reduced reproductive performance in limiting species recovery, and for aiding research programs focused on identifying what factors are compromising reproduction.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".