Experimental evidence of spatial memory and home range affinity in White-tailed Deer (<em>Odocoileus virginianus</em>)
Bibliographic record
Abstract
The role of spatial memory in the movement of animals through landscapes remains elusive. To examine spatial memory and home range affinity of White-tailed Deer (Odocoileus virginianus) in northeastern Minnesota during 1995–2007, I translocated 17 adult does with known home ranges to unfamiliar sites and radio-tracked them after their release. Twelve does wearing transmitting radio-collars returned to their home ranges. Death and collar expiration precluded determination of whether the remaining five does would have returned to home ranges. Three of five does wearing global positioning system collars traveled throughout hundreds of square kilometres, circling, backtracking, and returning to release sites, while two others exhibited directional movement for tens of kilometres. Four does that survived to parturition stopped traveling and moved at hourly rates similar to those of control does during the first three weeks of the typical fawn-rearing period, but continued traveling later. Their aberrant extensive travel before and after interruption by parturition suggests that they recognized they were in unfamiliar areas, demonstrating both their capacity and propensity to search for and occupy the familiar space of their individual home ranges. Their successful return to home ranges provided experimental evidence of spatial memory and further elucidated its pervasive role in White-tailed Deer spatial ecology.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".