Hypoxia 2023: physiological mechanisms of adaptation
Bibliographic record
Abstract
The biannual International Hypoxia Symposia are dedicated to bringing together the best basic scientific and clinical minds to focus on the integrative and translational biology of hypoxia (see http://www.hypoxia.net).The International Hypoxia Symposium was initially founded in 1979 by Charles Houston, Geoff Coates and John Sutton to enable scientists, clinicians, mountaineers and other interested individuals to share their experiences of the situations associated with a lack oxygen and the adaptations that, in some cases, allow reproduction and survival.Since 1999, under the leadership and vision of Rob Roach and Peter Hackett, the scientific excellence of the International Hypoxia Symposia has continued to flourish.In addition to dozens of productive scientific collaborations fostered in this congenial, cross-disciplinary environment, the 2023 meeting stimulated The Journal of Physiology to curate this Hypoxia 2023 Special Issue.We received a large number of submissions that studied physiological adaptation to life at terrestrial altitude.Below, the submissions are broadly split into three overlapping themes that are summarized next as a prelude to the Special Issue.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".