Integrating habitat use and population dynamics of moose in northern New Hampshire.
Bibliographic record
Abstract
ABSTRACT: The New Hampshire Fish and Game Department and the University of New Hampshire initiated research in northern New Hampshire to better understand population dynamics and seasonal habitat use of a moose population that has apparently stabilized, despite optimal habitat and modest harvest levels. In total, 94 moose were captured by helicopter (81 net-gunned and 13 tranquilized) in December 2001-2003 and 2 were darted at salt-licks in July of 2002. Capture mortality attributed to myopathy and injury was 4%. In comparison to measured reproduction during capture (63 and 100%), our ability to measure pregnancy by direct observations (69 and 100%) was validated in 2002-2003. Production was 0.82 and 0.85 calves per adult cow; rate of twinning was 20 and 10%. Calf mortality 2 months post-partum was similar (26 and 27%) each year. Annual mortality of adult/yearling moose was 27 and 12%. Hunting and vehicle collision mortality was 4 (all adult cows) and 6% (all calves but 1) each year. High annual winter calf mortality (38-43%) in late March and early April was associated with the combined effects of malnutrition and winter tick/lung nematodes. Winter home range size was not restricted, and composition of available habitat was similar across seasons although overlap was minimal between seasons. Consideration of habitat and population dynamics data suggests that ERWKGHQVLW\GHSHQGHQWDQGLQGHSHQGHQWIDFWRUVFRXOGEHLQAXHQFLQJWKHVWXG\SRSXODWLRQ
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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 | 0.000 | 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) | 0.001 | 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".