Estimation of harp seal (Pagophilus groenlandicus) pup production in the North Atlantic completed: results from surveys in the Greenland Sea in 2002
Bibliographic record
Abstract
Abstract From 14 March to 6 April 2002 aerial surveys were carried out in the Greenland Sea pack ice (referred to as the “West Ice”), to assess the pup production of the Greenland Sea population of harp seals, Pagophilus groenlandicus. One fixed-wing twin-engined aircraft was used for reconnaissance flights and photographic strip transect surveys of the whelping patches once they had been located and identified. A helicopter assisted in the reconnaissance flights, and was used subsequently to fly visual strip transect surveys over the whelping patches. The helicopter was also used to collect data for estimating the distribution of births over time. Three harp seal breeding patches (A, B, and C) were located and surveyed either visually or photographically. Results from the staging flights suggest that the majority of harp seal females in the Greenland Sea whelped between 16 and 21 March. The calculated temporal distribution of births were used to correct the estimates obtained for Patch B. No correction was considered necessary for Patch A. No staging was performed in Patch C; the estimate obtained for this patch may, therefore, be slightly negatively biased. The total estimate of pup production, including the visual survey of Patch A, both visual and photographic surveys of Patch B, and photographic survey of Patch C, was 98 500 (s.e. = 16 800), giving a coefficient of variation of 17.9% for the survey. Adding the obtained Greenland Sea pup production estimate to recent estimates obtained using similar methods in the Northwest Atlantic (in 1999) and in the Barents Sea/White Sea (in 2002), it appears that the entire North Atlantic harp seal pup production, as determined at the turn of the century, is at least 1.4 million animals per year.
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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 | 0.000 |
| 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".