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Record W4281759705 · doi:10.31234/osf.io/5jrcp

Postural adaptation to microgravity underlies fine motor impairment in astronauts' speech

2022· preprint· en· W4281759705 on OpenAlexaff
Arian Shamei, Márton Sóskuthy, Ian Stavness, Bryan Gick

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of SaskatchewanUniversity of British Columbia
FundersNational Institutes of Health
KeywordsAdaptation (eye)Vocal tractMotor controlUnificationVowelMovement (music)PsychologyPhysical medicine and rehabilitationComputer scienceCognitive psychologyNeuroscienceMedicinePhysicsSpeech recognitionAcoustics

Abstract

fetched live from OpenAlex

Understanding the role of anti-gravity behaviour in fine motor control is crucial to achieving a unified theory of motor control. We compare speech from astronauts before and immediately after microgravity exposure to evaluate the role of anti-gravity postures during fine motor skills. Here we show a generalized lowering of vowel spaces after space travel, which suggests a generalized postural shift of the articulators. Biomechanical modelling of the vocal tract in simulated 1g and 0g conditions supports this analysis – the jaw and tongue are pulled down in 1g, but movement trajectories of the tongue are otherwise unaffected. These results demonstrate the role of anti-gravity posture in fine motor behaviour and provide a basis for the unification of motor control models across domains.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.053
GPT teacher head0.373
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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