Spatial Memory in the North American Red Squirrel (Tamiasciurus hudsonicus)
Bibliographic record
Abstract
For animals, it is important to use spatial information in their environment in order to survive and reproduce. Spatial memory is important for animals that rely on caching and recovering food during times of scarcity. We explored two questions. First, whether squirrels are capable of spatial memory through the use of an associative-learning task. Here we spent time training individuals to approach and find the reward in a spatial array. Second, whether squirrels can recall a specific location with which they associated food recovery. If the duration and precision of memory are the mechanism underlying cache recovery, squirrels should learn to associate recovery of food with a specific location. We predict that squirrels will (a) learn the task, by approaching and recovering from a precise location, and (b) show evidence of long-term memory for the precise location after intervals of one, two, four, and six days. Faculty Mentor: Shannon Digweed Department: Psychology (Honours)
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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 | 0.000 | 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) | 0.002 | 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".