HOW MANAGEMENT UNIT LICENSE QUOTAS RELATE TO POPULATION SIZE, DENSITY, AND HUNTER ACCESS IN NEWFOUNDLAND
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We recommend introducing habitat-based moose density as a management tool to be used in annual quota setting. We illustrate our recommendation with the case of Newfoundland, where moose densities are much higher than elsewhere in North America, and have led to local areas of habitat deterioration and subsequent population decline. We suggest more emphasis be placed on relationships between local densities of moose and reported hunter kill locations to stabilize populations. We calculated both moose density and moose-kill density using estimates of forest and scrub cover in management units surveyed between 1985 and 2001, comparing aerial surveys with license sales for the same year WRKXQWHUVXFFHVV���,QWKH�oUVWSDUWRIRXUVWXG\�SHULRG��OLFHQ
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.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it