Associations between Woodland Caribou telemetry data and Landsat TM spectral reflectance
Bibliographic record
Abstract
Woodland Caribou Rangifer tarandus caribou habitat mapping in northern Alberta, Canada is incomplete and imprecise, as habitat relationships are not fully understood, and land cover mapping is neither consistent nor complete. Spectral information obtained through remote sensing observations makes possible the evaluation of Woodland Caribou habitat use over large areas. With the use of Global Positioning System (GPS) collars fitted on the animals, correlations between satellite observations and Woodland Caribou locations were studied. This study examines Landsat 5 Thematic Mapper imagery of the Wabasca region of northern Alberta in relation to a dataset containing nearly 100 000 locations acquired from GPS radio-collars and approximately 5000 locations acquired from Very High Frequency (VHF) radio-collars. The intent was to determine if spectral signatures measured by remote sensing satellites could be related to habitat use or avoidance by caribou, and to use this knowledge to predict caribou habitat selection in areas where there are no collared animals. The analysis presented in this paper provides a new perspective for the analysis of large and complex habitat selection datasets and opens new opportunities for the implementation of better and more comprehensive conservation policies in boreal environments. The methodology and habitat associations presented in this paper are being used in northern Alberta to advance caribou conservation.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".