Determining Social Rank in Ungulates: A Comparison of Aggressive Interactions Recorded at a Bait Site and under Natural Conditions
Bibliographic record
Abstract
Abstract Researchers often assume that dyadic interactions at bait sites have similar outcomes to those occurring under natural conditions, but this assumption has seldom been tested. I used aggressive interactions recorded during 1994–97 among marked mountain goats (Oreamnos americanus) to compare dyadic relationships near an artificial salt lick with those observed under natural conditions. I also examined how observations recorded at the lick affected the structure of dominance matrices. The probability of winning an encounter was strongly and positively related to age, both under natural conditions and at the salt lick. The proportion of interactions that adult females lost to 2‐yr‐olds and the proportion won by the youngest individual among adult females, however, more than doubled at the salt lick compared to natural conditions. Two‐year‐old females were 22 times more likely to win interactions against 2‐yr‐old males at the lick than under natural conditions. A decrease in the directional consistency index revealed that the outcomes of repeated encounters of the same dyad were more inconsistent at the salt lick than elsewhere. When interactions recorded at the lick were added to female dominance matrices, the number of inconsistencies more than doubled and the strength of the inconsistencies increased 2–8 times compared to matrices restricted to interactions recorded under natural conditions. Interactions seen at the salt lick caused substantial changes in the hierarchical rank of individual goats. Because interaction rates were high and animals were very concentrated at the trap site, individual recognition may have been difficult, explaining the differences observed in dyadic relationships at the lick compared to natural conditions.
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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 | 0.002 | 0.001 |
| 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".