Personality and fitness consequences of flight initiation distance and mating behavior in subdominant male reindeer (<i>Rangifer tarandus</i>)
Bibliographic record
Abstract
Abstract Animal personality has been studied extensively in recent years, yet multidimensionality in tendencies of risk‐related behavior, and the role of such consistency from a mating tactics perspective, is yet to be investigated. We used a semi‐domesticated herd of reindeer (Rangifer tarandus) to examine individual subdominant male propensity to risk mating attempts on guarded females, as well as flight initiation distance (FID), within the personality paradigm to elucidate potential fitness consequences of consistency from an adaptive perspective. Data were collected at the Kutuharju Reindeer Research Station in Kaamanen, Finland, where measures of personality were generated using field observation data based on the relative frequency of dominant male–subdominant male agonistic interactions over 4 years and subdominant males' FID measured over 1 year. Individual propensity for transient mating attempts was not significantly repeatable and did not significantly predict reproductive success or somatic cost during the mating season. Individuals varied consistently in FID, and although repeatable, FID was not related to reproductive success or somatic cost. Proximate state‐dependent or social mechanisms may be driving decision‐making with respect to mating effort, whereas consistent between‐individual differences in FID may be maintained by mechanisms unrelated to life‐history trade‐offs involving productivity.
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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".