Annual and monthly range fidelity of female boreal woodland caribou in respons to petroleum development
Bibliographic record
Abstract
Petroleum-sector development in northern Alberta, Canada has been implicated as one factor influencing the decline of boreal woodland caribou (Rangifer tarandus caribou). Previous research showed that caribou are farther from petroleum-sector disturbances within their home range than expected. As petroleum development increases, the distance caribou can selectively place themselves relative to industrial disturbance must decrease, because distances between disturbances decrease. Conceptually, the number of local disturbances becomes so large that caribou either abandon their local avoidance behaviour or leave their traditional home range. We evaluated whether an intense petroleum- development event in northern Alberta was sufficient to result in home range abandonment by female woodland caribou. Using well locations as an index of petroleum development, we found that caribou studied from 1992 to 2000 did not change their annual or monthly range fidelity as a function of development intensity. Caribou remained in peatland complexes containing a large number of petroleum-sector disturbances rather than move to new areas, presumably because the risks of dispersing across upland habitat to reach other suitable habitat are high. Such range fidelity may have fitness consequences for woodland caribou if they suffer greater predation in areas where petroleum development is occurring.
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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 | 0.001 |
| 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".