Population demography of high arctic caribou on Banks and Melville Islands
Bibliographic record
Abstract
Caribou numbers, Rangifer tarandus pearyi, (excluding calves) on Banks Island were estimated (standard error of the estimate) at 1005 (SE±133) in 1992, 709 (SE±128) in 1994 and 436 (SE±71) in 1998; no paired estimates were different (P<0.05). On Melville Island caribou numbers were similar in 1987 and 1997 with estimates of 729 (SE±104) and 787 (SE±97), respectively. We conducted annual sex and age classification surveys during July on Banks Island from 1994-2000 and on Melville Island from 1998-2000. The number of calves per 100 >two-year-old females ranged from 24.0 in 1994 to 74.3 in 1998 on Banks Island, and from 44.8 in 1999 to 80.0 in 1998 on Melville Island. Recruitment rate ranged from 18.6% during 1997/1998 to 27.5% during 1999/2000 on Banks Island and from 16.7% during 1997/1998 to 25.0% during 1999/2000 on Melville Island. There has been an increasing trend in the rate of recruitment on both islands during the last three years of the study.
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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 | 0.001 | 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".