The evaluation of cardiac function across the health spectrum under diverse conditions of physiological stress: introduction
Bibliographic record
Abstract
In this paper we introduce 3 papers resulting from a symposium evaluating cardiac function across the health spectrum under varied conditions of physiological stress. Esch et al. (Appl. Physiol. Nutr. Metab. 32: this issue) evaluate the potential role the pericardium plays on diastolic filling in endurance-trained athletes. These authors reveal how pericardial remodelling may explain (in part) why endurance athletes can achieve superior stroke volumes during exercise while also being increasingly susceptible to orthostatic intolerance. Warburton et al. (Appl. Physiol. Nutr. Metab. 32: this issue) review the central and peripheral mechanisms responsible for the exercise intolerance of chronic heart failure. They also reveal the important therapeutic effects of exercise rehabilitation for the treatment of heart failure. Scott et al. (Appl. Physiol. Nutr. Metab. 32: this issue) highlight the cardiovascular consequences of the gravitational stress placed upon pilots and the countermeasures commonly used. Collectively, these articles highlight the importance and difficulty of assessing cardiac function under varied conditions of physiological stress.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".