Selection of Agricultural Foods by Eastern Grey Squirrels (<i>Sciurus carolinensis</i>): Implications for a New Introduction in British Columbia
Bibliographic record
Abstract
The recent introduction of the Eastern Grey Squirrel (Sciurus carolinensis) into south-central British Columbia occurred within an important agricultural zone. As repercussions for the fruit-growing sector are currently unknown, we conducted trials with captive squirrels to understand the range of fruits consumed and their references. The squirrels consumed a portion of every food item offered, although the order in which the foods were used was inconsistent (with sharp contrasts between animals). Of the fruit types offered, apples appeared to be of greatest overall interest. However, seeds and nuts tended to be used first when presented in combination with fruit, suggesting opportunities to use these food types to deflect or remove Eastern Grey Squirrels from orchard crops. We caution that our results may not reflect the food items that free-ranging Eastern Grey Squirrels will target or disregard once densities in the introduced population become higher and the availability of food on a local scale begins to exert an effect.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".