ASSESSING AGE OF HARVESTED MOOSE PRIOR TO POPULATION DECLINES IN BRITISH COLUMBIA
Bibliographic record
Abstract
Moose populations in parts of British Columbia, Canada have been declining since about the mid-2000s with the licensed harvest dropping by more than half from 1987 to 2014. A tooth reporting program for harvested moose from 1982 to 2003 enabled us to assess the relationship between age of harvested moose and 1) time (1982–2003), 2) level of licensed harvest of bulls and cows, and 3) estimated populations prior to declines with age data collected after decline in the province. We used age data determined from cementum annuli of teeth collected from hunter returns from 72,888 moose (n = 57,376 bulls and n = 15,512 cows). We found average age of harvested bulls and cows to be 3.32 ± 0.02 and 4.99 ± 0.06 years, respectively, similar to ranges reported elsewhere in western North America. Age of bulls declined linearly by year, whereas age of cows declined in the latter half of the study period. The average age of cows harvested from 1983 to 2003 prior to the population decline (n = 2,016; mean = 3.84 years, SD = 3.03) was 7 years younger than that of a small sample of cows dying of multiple causes (harvest and natural) during the decline (n = 47; mean = 10.93 years, SD = 3.72). We acknowledge the logistical and financial constraints required to gather a representative sample of teeth from harvested moose, but recommend reimplementation of a tooth collection program to provide continuous information on the age structure of moose populations to help guide management decisions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".