Sea-ice crossings by caribou in the south-central Canadian Arctic Archipelago and their ecological importance
Bibliographic record
Abstract
The islands of the Canadian Arctic Archipelago lie immediately north of mainland North America in the Arctic Ocean. They are surrounded by ice for most of each year. Caribou (Rangifer tarandus) cross the sea ice in seasonal migrations among the islands and between the mainland and Arctic Islands. We compiled observations of 1272 discrete caribou crossings on the sea ice of northeastern Franklin Strait, Bellot Strait, Peel Sound and Baring Channel in the south-central Canadian Arctic Archipelago during four May—June search periods from 1977 to 1980. We clustered the 850 caribou trails found on the sea ice of northeastern Franklin Strait and on outer Peel Sound as 73 sea-ice crossing sites. We investigated whether caribou at the origin of a sea-ice crossing site could see land on the opposite side at the potential terminus. We measured the straight-line distance from where the caribou first came onto the ice (origin) to the first possible landfall (potential terminus). Potential termini were geodetically visible to caribou from elevated terrain near 96% of the origins of the 73 sea-ice crossing sites and still visible at sea-level at the origins on 68%. Caribou are able to take advantage of seasonal use of all of the islands and the peninsula by making sea-ice crossings, thereby helping to increase the magnitudes and durations of population highs and reduce their lows. Knowledge of these alternative pat¬terns of use made possible by sea-ice crossings is necessary to fully understand the population dynamics of these caribou and the importance of possible future changes in ice cover.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".