Bibliographic record
Abstract
The human spleen shows a decrease in volume of around 40% early during vigorous exercise and in response to other stressful stimuli such as maximal apnoea and the breathing of hypoxic gas mixtures. Contraction seems an active response, mediated by alpha-adrenergic fibres in the splenic nerve. Given the relatively small size of the human spleen, the effect upon physical performance is likely to be small; the augmentation of total blood volume is <2%, and even taking account of other causes of haemoconcentration during vigorous exercise, the increase of haematocrit is <10%. However, one of two studies suggested that the haemoconcentration may be sufficient to cause errors in the traditional method for calculating exercise-induced changes of plasma volume. The spleen also contributes leucocytes and platelets to the general circulation as part of the "fight or flight" reaction to stressors. The mobilisation of leucocytes proceeds more slowly than that of the red cells; it depends not only upon an active contraction of the spleen, but also a modulation of leucocyte adhesion molecules. Splenectomy impairs exercise performance in horses, but human performance data are lacking; overall health effects seem minimal, and many patients live many years after removal of their spleens.
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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".