MétaCan
Menu
Back to cohort
Record W3128638433 · doi:10.26443/mjm.v6i1.555

Psychological and Human Factors in Long Duration Spaceflight

2020· article· en· W3128638433 on OpenAlexvenueno aff
Ephimia Morphew

Bibliographic record

VenueMcGill Journal of Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicSpaceflight effects on biology
Canadian institutionsnot available
Fundersnot available
KeywordsSpaceflightCrewStressorHabitabilityHuman spaceflightAeronauticsHuman healthPsychologyMedicineApplied psychologyEngineeringSpace explorationClinical psychologyEnvironmental healthAerospace engineeringPhysics

Abstract

fetched live from OpenAlex

The spaceflight environment is characterized by temperature extremes, microgravity, solar and galactic cosmic radiation, lack of atmospheric pressure, and high-speed micrometeorites. While these factors induce a host of physiological, biomedical, and environmental stressors to flight crews, long duration spaceflight has revealed an additional group of stressors that impact crew performance and health. This paper will provide members of the medical community with a basic understanding of human-related stressors in the spaceflight environment, the effects of these stressors, and the role that the behavioral sciences (e.g., psychology, human factors, sociology, habitability) play in supporting crew health in space. Some of the current tools and methodologies used by behavioral scientists for countering spaceflight stressors and promoting crew health, productivity, and mission success will also be discussed.

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)0.001
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.058
GPT teacher head0.360
Teacher spread0.302 · 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

Citations76
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueMcGill Journal of MedicineSame topicSpaceflight effects on biologyFrench-language works237,207