Bibliographic record
Abstract
ABSTRACT P crit – generally defined as the PO2 below which the animal can no longer maintain a stable rate of O2 consumption (ṀO2), such that ṀO2 becomes dependent upon PO2 – provides a single number into which a vast amount of experimental effort has been invested. Here, with specific reference to water-breathers, I argue that this focus on the Pcrit is not useful for six reasons: (1) calculation of Pcrit usually involves selective data editing; (2) the value of Pcrit depends greatly on the way it is determined; (3) there is no good theoretical justification for the concept; (4) Pcrit is not the transition point from aerobic to anaerobic metabolism, and it disguises what is really going on; (5) Pcrit is not a reliable index of hypoxia tolerance; and (6) Pcrit carries minimal information content. Preferable alternatives are loss of equilibrium (LOE) tests for hypoxia tolerance, and experimental description of full ṀO2 versus PO2 profiles accompanied by measurements of ventilation, lactate appearance and metabolic rate by calorimetry. If the goal is to assess the ability of the animal to regulate ṀO2 from this profile in a mathematical fashion, promising, more informative alternatives to Pcrit are the regulation index and Michaelis–Menten or sigmoidal allosteric analyses.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.005 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".