Control of Breathing and Adaptation to High‐altitude Hypoxia in Deer Mice ( <i>Peromyscus maniculatus</i> )
Bibliographic record
Abstract
High‐altitude environments pose multiple challenges, such as cold temperatures and low partial pressures of oxygen. This study compared the control of breathing and pulmonary gas exchange in populations of deer mice with highland and lowland ancestry to determine the physiological specializations important for living in high‐altitude environments. The hypoxic ventilatory response was measured using whole‐body plethysmography in response to step‐wise decreases in inspired oxygen fraction, from 21% to 8%, in mice acclimated to normoxia or hypobaric hypoxia (simulating the hypoxia at ~4300 m elevation). Total ventilation was similar between populations, but highland mice acclimated to normoxia had a more effective breathing pattern than lowland mice acclimated to normoxia, characterized by deeper less frequent breaths at a given total ventilation. Hypoxia acclimation had no effect on breathing pattern in highland mice, but it increased tidal volume and decreased breathing frequency in lowland mice. Highland ancestry and hypoxia acclimation also affected respiratory water loss and thermoregulatory responses to hypoxia. Therefore, both highland ancestry and hypoxia acclimation influence the control of breathing and pulmonary gas exchange in deer mice. Supported by NSERC of Canada.
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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".