Canada Jay (<i>Perisoreus canadensis</i>) harvesting and caching fruits of Thin-leaved Snowberry (<i>Symphoricarpos albus</i>)
Bibliographic record
Abstract
On 17 September 2021, we observed three Canada Jay (Perisoreus canadensis) harvesting and caching Thin-leavedSnowberry (Symphoricarpos albus) fruits in a mixed conifer forest in western Montana, USA. Thin-leaved Snowberry hasnot been reported previously in their diet. During 3 min of direct observation, each jay harvested snowberries similarly and cached them on the trunks of nearby pines. In each case (11 caches), the jay flew by the snowberry shrubs twice, plucking a fruit while airborne, landing on the ground between passes, the first fruit carried in the throat, the second in the bill. The jays then landed, most often out of view on tree trunks, but, nevertheless, appeared to cache the fruits each time. One cache observed in the making contained two harvested fruits wedged in a crevice on the trunk and covered with a flake of bark. Thin-leaved Snowberry is considered a low-quality fall-ripening fruit because of the small energy gain for each fruit consumed. Nevertheless, the energy density of snowberries (16.65 kJ/g dry mass) collected at the same location in October exceeded that required by non-migratory Canada Jays for daily maintenance during winter. It is unlikely jays could cache enough fruits each day to sustain them for several winter months. Instead, snowberries could be an important and readily available autumn and winter food for Canada Jays resident in this region when used to supplement other stored foods with greater energy, fat, and protein content.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".