Bibliographic record
Abstract
Cranial measurements were taken from 378 Ovis skulls (258 male, 120 female), covering most subspecies of wild sheep. Horn core length and circumference data were used to estimate the core surface. This highly vascularized plexus constitutes the radiating area. A simple index of heat-exchange capacity was calculated by dividing the combined surfaces of two horn cores by the mass of the animal. This index provided a standard by means of which different types of sheep could be compared, as well as allowing the detection of correlations with environmental gradients, which would point to a thermoregulatory role for horn cores. It can be assumed that, for sheep living in cold climates, heat conservation is important, while for those living in hot environments, enhanced heat dissipation would be advantageous. Our data confirm this hypothesis. The thinhorn sheep (Ovis dalli and Ovis nivicola) of subarctic and arctic northwestern North America and northern Siberia have the smallest horn cores, with indices of 6.9-7.3 cm2/kg, while desert-dwelling types have indices of more than twice these values. For instance, the desert subspecies of the American bighorns (Ovis canadensis nelsoni, Ovis canadensis mexicana, Ovis canadensis cremnobates) have indices ranging from 15.1 to 16.5 cm2/kg. Other sheep types have indices of intermediate sizes. It is our position that this evolutionary trend to vary core size in response to ambient temperature is independent of a parallel trend to increase horn size for the benefit of enhancing reproductive success.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".