Sex as a biological variable for cardiovascular physiology
Bibliographic record
Abstract
There have been ongoing efforts by federal agencies and scientific communities since the early 1990s to incorporate sex and/or gender in all aspects of cardiovascular research. Scientific journals provide a critical function as change agents to influence transformation by encouraging submissions for topic areas, and by setting standards and expectations for articles submitted to the journal. As part of ongoing efforts to advance sex and gender in cardiovascular physiology research, the American Journal of Physiology-Heart and Circulatory Physiology recently launched a call for papers on Considering Sex as a Biological Variable. This call was an overwhelming success, resulting in 78 articles published in this collection. This review summarizes the major themes of the collection, including Sex as a Biological Variable Within: Endothelial Cell and Vascular Physiology, Cardiovascular Immunity and Inflammation, Metabolism and Mitochondrial Energy, Extracellular Matrix Turnover and Fibrosis, Neurohormonal Signaling, and Cardiovascular Clinical and Epidemiology Assessments. Several articles also focused on establishing rigor and reproducibility of key physiological measurements involved in cardiovascular health and disease, as well as recommendations and considerations for study design. Combined, these articles summarize our current understanding of sex and gender influences on cardiovascular physiology and pathophysiology and provide insight into future directions needed to further expand our knowledge.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".