Bibliographic record
Abstract
The critical O<sub>2</sub> tension (<i>P</i><sub>crit</sub>) is the lowest <i>P</i><sub>O<sub>2</sub></sub> at which an animal can maintain some benchmark rate of O<sub>2</sub> uptake (<i>Ṁ</i><sub>O<sub>2</sub></sub> ). This <i>P</i><sub>O<sub>2</sub></sub> has long served as a comparator of hypoxia tolerance in fishes and aquatic invertebrates, but its usefulness in this role, particularly when applied to fishes, has recently been questioned. We believe that <i>P</i><sub>crit</sub> remains a useful comparator of hypoxia tolerance provided it is determined using the proper methods and hypoxia tolerance is clearly defined. Here, we review the available methods for each of the three steps of <i>P</i><sub>crit</sub> determination: (1) measuring the most appropriate benchmark <i>Ṁ</i><sub>O<sub>2</sub></sub> state for <i>P</i><sub>crit</sub> determination (<i>Ṁ</i><sub>O<sub>2</sub>,std</sub>, the <i>Ṁ</i><sub>O<sub>2</sub></sub> required to support standard metabolic rate); (2) reducing water <i>P</i><sub>O<sub>2</sub></sub> ; and (3) calculating <i>P</i><sub>crit</sub> from the <i>Ṁ</i><sub>O<sub>2</sub></sub> versus <i>P</i><sub>O<sub>2</sub></sub> curve. We make suggestions on best practices for each step and for how to report <i>P</i><sub>crit</sub> results to maximize their comparative value. We also discuss the concept of hypoxia tolerance and how <i>P</i><sub>crit</sub> relates to a fish's overall hypoxia tolerance. When appropriate methods are used, <i>P</i><sub>crit</sub> provides useful comparative physiological and ecological information about the aerobic contributions to a fish's hypoxic survival. When paired with other hypoxia-related physiological measurements (e.g. lactate accumulation, calorimetry-based measurements of metabolic depression, loss-of-equilibrium experiments), <i>P</i><sub>crit</sub> contributes to a comprehensive understanding of how a fish combines aerobic metabolism, anaerobic metabolism and metabolic depression in an overall strategy for hypoxia tolerance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".