A reexamination of the metabolic response of the genus <i>Peromyscus</i> to a climatic gradient
Bibliographic record
Abstract
An earlier analysis demonstrated that the mass-independent energy expenditure of five species of the genus Peromyscus Gloger, 1841 decreased with increasing aridity along a mesic–xeric climatic gradient. Each species was represented by two populations that were located along the gradient. These data are reexamined with new analytical techniques. A mass analysis accounted for the basal rates of six populations within 10% of the measured rates. The analysis accounted for the rates of all eight populations within 10% when it included the gradient. An apparent limit to this response may restrict the geographic distributions of Peromyscus in desert environments, which may have distributional and survival consequences with climate change. One species, the California mouse (Peromyscus californicus (Gambel, 1848)), did not conform to the analysis of the other species, which may reflect the presence of unidentified biological or environmental factors present in this and the other species. A successful analysis of the energy expenditures of species must include their characteristics and those of the environment in which they live because these are the factors that define species and their performance. To determine the effectiveness of an analysis, the estimated expenditures are compared with the measured expenditures, acceptable estimates being within 10% of the measured expenditures.
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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 | 0.001 | 0.001 |
| 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".