Ideal free eagles: Bald Eagle (<i>Haliaeetus leucocephalus</i>) distribution in relation to Pacific salmon (<i>Oncorhynchus</i> spp.) availability on four spawning rivers
Bibliographic record
Abstract
The movement of individuals according to the availability of resources has a fundamental effect on animal distributions. In the Pacific Northwest, Bald Eagles (Haliaeetus leucocephalus (Linnaeus, 1766)) rely heavily on scavenging opportunities during the non-breeding period, and their distribution and movements are thought to be strongly influenced by the availability of post-spawning Pacific salmon (genus Oncorhynchus Suckley, 1861) carcasses. We surveyed the abundance of eagles and salmon on four adjacent rivers on Vancouver Island, British Columbia, Canada, during the 2017 fall spawning season. Salmon began to arrive in late September, peaked in abundance in mid-November, and were absent after early December. The seasonal progression of Bald Eagle abundance matched that of salmon carcass availability. The slope of proportional eagle–salmon relationship was significantly positive, though lower than the 1:1 match predicted by Ideal Free Distribution theory. The numerical response of Bald Eagles to salmon abundance was elevated on one of the rivers, potentially due to physical features such as sandbars and mudflats that increased the availability of carcasses and provided access points for eagles.
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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".