Black-tailed prairie dog (Cynomys ludovicianus) awareness of neighbours’ vigilance is spatially explicit
Bibliographic record
Abstract
Black-tailed prairie dogs, Cynomys ludovicianus, gauge neighbour vigilance through jump yipping, a contagious, multimodal display where individuals vocalize while jumping upward. Jump-yip bouts were recorded using three camcorders across 27 sites within the Dakotas to examine how instigator location and spatiotemporal pattern of conspecific response within bouts influence instigator vigilance, thereby testing whether instigator knowledge of conspecific vigilance is spatially explicit. Video files were analyzed to determine if instigators disproportionately devoted personal vigilance following jump-yip bouts toward areas of conspecific non-responsiveness over areas with conspecific response. Paired-sample tests indicated that instigators oriented vigilance toward non-responsive areas significantly more than areas of responsiveness after both current (Z = -4.74, P = 0.0001) and past jump-yip bouts (Z = 0.42, P = 0.0001). Instigators direct personal vigilance toward areas where predators may go undetected, demonstrating spatiotemporal awareness of conspecific vigilance, and thus utilizing both public and personal information to minimize predation risk.
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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) | 0.001 | 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".