Human disturbance, nursing behaviour, and lactational pup growth in a declining southern elephant seal (<i>Mirounga leonina</i>) population
Bibliographic record
Abstract
We studied lactation behaviour in relation to pup growth in southern elephant seals (Mirounga leonina) at Macquarie Island, and compared harems in areas of high and low human presence to determine if there is an effect attributable to human activities, including scientific research. Pup weaning mass, a known correlate of firstyear survival, was positively influenced by suckle bout durations during early and middle lactation and by maternal aggression during late lactation; no other behavioural variables were associated with weaning mass. In the area of high human presence, we observed from a distance the behaviour of motherpup pairs directly before, during, and after visits to harems by other researchers. Alertness was raised threefold in the presence of people but quickly returned to predisturbance levels after their departure; there were no significant short-term effects on other behavioural variables. In the areas of high and low human presence, we observed the undisturbed behaviour of the seals in the absence of other people. No significant differences in any behavioural variables examined were found, indicating no long-term changes in behaviour resulting from human presence. Human disturbance therefore appears not to have significantly contributed to the population decline observed at Macquarie Island, but the conclusion requires caution given the fairly low power of our analyses.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".