Observations of Bobcats, <em>Lynx rufus</em>, Hunting Black-Tailed Prairie Dogs, <em>Cynomys ludovicianus</em>, in Western South Dakota
Bibliographic record
Abstract
There is a paucity of scientific literature describing Bobcat (Lynx rufus) hunting strategies. I document 13 observations of Bobcats hunting Black-tailed Prairie Dogs (Cynomys ludovicianus) in western South Dakota. In all cases the Bobcats stationed themselves next to a prairie dog mound in an attempt to ambush prairie dogs emerging from their burrows. In eight cases the Bobcats successfully captured a prairie dog emerging from the burrow, in one case the Bobcat turned and captured a prairie dog that had walked up behind it, and in the other cases the Bobcats lunged at the burrow openings, but did not capture a prairie dog. There were two variations of the tactic: in some cases Bobcats entered a colony prior to prairie dog emergence and stationed themselves next to a mound, whereas in other cases Bobcats stationed themselves next to a burrow that a prairie dog had just escaped to. One Bobcat appeared to have waited next to the same mound for at least 7.5 hr. Prairie dogs may comprise a large portion of a Bobcat's winter diet in landscapes where prairie dog colonies exist in close proximity to badlands or woody cover.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".