Bibliographic record
Abstract
The fast–slow continuum hypothesis explains life-history traits as reflecting the causal influence of mortality patterns in interaction with trade-offs among traits, particularly more reproductive effort at a cost of shorter lives. Variation among species of different body sizes produce more or less rapid life cycles (respectively, from small to large species), but the fast–slow continuum remains for birds and mammals when body-size effects are statistically removed. We tested for a fast–slow continuum in mammalian carnivores. We found the above trade-offs initially supported in a sample of 85 species. Body size, however, was strongly associated with phylogeny (ρ = 0.79), and thus we used regression techniques and independent contrasts to make statistical adjustments for both. After adjustments, the life-history trade-offs were not apparent, and few associations of life-history traits were significant. Litter size was negatively associated with age at maturity, but slightly positively associated with offspring mass. Litter size and mass were negatively associated with the length of the developmental period. Gestation length showed weak but significant negative associations with age at maturity and longevity. We conclude that carnivores, despite their wide range of body sizes and variable life histories, at best poorly exhibited a fast–slow continuum.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".