Experimental bed rest as a model to investigate mechanisms of, and countermeasures against, microgravity and disease‐free inactivity
Bibliographic record
Abstract
More humans are now entering space than ever before, owing to significant investment from governmental and commercial agencies looking ambitiously to expand the reach of humanity beyond low Earth orbit, involving habitation of a permanent base on the surface of the Moon ahead of the horizon goal, a crewed mission to the red planet, Mars.With the advent of long-duration interstellar travel, there is mounting pressure to gain a better understanding of the functionally integrated physiological responses to, and countermeasures that mitigate against, the maladaptive changes incurred by microgravity and physical inactivity.Owing to the technical, logistical and financial costs associated with conducting spaceflight research, 6 • head-downtilt bed rest (HDBR), first introduced by a Soviet team led by Genin and Kakurin (1972), has become the mainstay ground-based analogue of microgravity (Hargens & Vico, 2016).In this issue of Experimental Physiology, Hajj-Boutros et al. (2024) comprehensively detail the first Canadian study (supported by the Canadian Space Agency, Canadian Institutes of Health Research and
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".