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Record W2019012517

The effects of background noise on cognitive performance during a 70 hour simulation of conditions aboard the International Space Station.

2004· article· en· W2019012517 on OpenAlexaff
D. G. Smith, Joseph V. Baranski, Megan M. Thompson, S. M. Abel

Bibliographic record

VenuePubMed · 2004
Typearticle
Languageen
FieldMedicine
TopicSpaceflight effects on biology
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsQUIETInternational Space StationVigilance (psychology)Noise (video)CognitionAudiologyMoodEffects of sleep deprivation on cognitive performancePsychologyAffect (linguistics)PerceptionNoise levelSimulationMedicineSocial psychologyAeronauticsComputer scienceEngineeringCognitive psychologyCommunicationArtificial intelligencePsychiatry
DOInot available

Abstract

fetched live from OpenAlex

A total of twenty-five subjects were cloistered for a period of 70 hours, five at a time, in a hyperbaric chamber modified to simulate the conditions aboard the International Space Station (ISS). A recording of 72 dBA background noise from the ISS service module was used to simulate noise conditions on the ISS. Two groups experienced the background noise throughout the experiment, two other groups experienced the noise only during the day, and one control group was cloistered in a quiet environment. All subjects completed a battery of cognitive tests nine times throughout the experiment. The data showed little or no effect of noise on reasoning, perceptual decision-making, memory, vigilance, mood, or subjective indices of fatigue. Our results suggest that the level of noise on the space station should not affect cognitive performance, at least over a period of several days.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.269
Teacher spread0.255 · 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 designSimulation or modeling
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

Citations53
Published2004
Admission routes1
Has abstractyes

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