Sensory network segregation as a predictor of post spaceflight balance impairments and sensory re-weighting
Bibliographic record
Abstract
Exposure to microgravity results in transient sensorimotor performance declines when crewmembers return to Earth, likely due to sensory re-weighting. This poses performance risks following gravitational transitions, such as arriving on the Moon or Mars. Here, we examined whether sensory brain network segregation (how independently a given network functions) in astronauts prior to an International Space Station mission would predict balance post-flight. Intraclass correlation analysis showed high test-retest reliability for all sensory network segregation measures. Indices of the Parietal Operculum 2 network (OP2) segregation pre-flight significantly predicted balance performance. Specifically, greater segregation predicted poorer balance on day one following return to Earth (Left OP2), better balance four days post-flight (Left and Right OP2) and greater balance improvements from one to four days post-flight. Results suggest that OP2 segregation may index plasticity of sensory weighting processes; that is, the degree of vestibular input down-weighting measured initially post-flight and extent of recovery over subsequent four days.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".