Bibliographic record
Abstract
In this note, I report on my observations of a pair of Canada Jays (Perisoreus canadensis) gathering live engorged female Winter Ticks (Dermacentor albipictus) from the recent bed of a yearling Moose (Alces alces) and flying into the adjacent woods to cache the ticks before returning for more. The Moose bed was on snow and contained loose hair and blood-stained snow as well as the engorged ticks. I found 12 additional beds on snow during the next 48 h within 250 m of the original bed, and all contained loose hair and blood-stained snow, but no ticks. Jays may routinely visit Moose beds on snow in spring because they recognize them as a potential source of food. Moose, however, may not be present during spring in many jay territories, so access to engorged ticks at beds is probably opportunistic and unreliable.
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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".