Hunting success of wintering Swainson's hawks: environmental effects on timing and choice of foraging method
Bibliographic record
Abstract
We examined the predatory behavior of Swainson's hawks (Buteo swainsoni Bonaparte, 1838) wintering in the Argentine pampas. Aerial and ground foraging were the main hunting methods employed by hawks in this region. The overall hunting success of hawks preying on insects was 50% and age-related differences in hunting success were not significant. The Swainson's hawks, however, hunted more successfully in the air (65% of prey capture attempts) than on the ground (42%). Aerial hunting while soaring was the most successful hunting method based on the number of prey captured per energy unit. Based on the analysis of prey consumed by hawks during the study period, grasshopper species with poor flight capabilities were available in the air as a consequence of the vertical air motion. With regards to daily activity patterns, the time that a hawk spent using each hunting method was not proportional to the cost ratio associated with each method. Hawks foraged in the air only during midday hours when weather conditions permitted the formation of thermals. Thus, the use of soaring flights and the availability of prey in the air were constrained by the physical environment, and hawks could only exploit airborne food sources during limited periods of the day.
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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 | 0.000 |
| 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".