The Mountain Caribou in Managed Forests Program: Integrating fore- stry and habitat management in British Columbia.
Bibliographic record
Abstract
forest stands be managed, t h r o u g h s i lv icul tural systems and habitat enhancement techniques, to provide both t imber and car ibou habitat? T h e program includes radiotelemetry, habitat capabil i ty mapping, habitat manage-ment trials, and development of an integrated strategy. T h e management trials are aimed at mainta in ing arbo-real lichens and other key habitat attributes i n managed stands. T h e strategy development c o m p o n e n t i n v o l-ves wi ld l i fe biologists and foresters i n developing and implement ing solutions to logging-caribou confl icts. Key words: Rangifer, caribou, Br i t ish C o l u m b i a, habitat management, forestry, partial cutting, confl ict ing interests. Rangifer, Special Issue N o. 7: 130—136
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".