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Record W2089836567 · doi:10.7205/milmed-d-10-00093

A Comparison of Cognitive Performance Decreases During Acute, Progressive Fatigue Arising From Different Concurrent Stressors

2010· article· en· W2089836567 on OpenAlexaff
Donovan L. Fogt, John Kalns, Darren J. Michael

Bibliographic record

VenueMilitary Medicine · 2010
Typearticle
Languageen
FieldPsychology
TopicSleep and Work-Related Fatigue
Canadian institutionsHyperion Technologies (Canada)
FundersCenters for Disease Control and PreventionU.S. Department of Defense
KeywordsStroop effectEffects of sleep deprivation on cognitive performanceCognitionMoodStressorAffect (linguistics)Profile of mood statesAudiologyCognitive testSleep deprivationWorking memoryPsychologyMedicineClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Fatigue is known to impair cognitive performance, but it remains unclear whether concurrent common stressors affect cognitive performance similarly. We used the Stroop Color-Word Conflict Test to assess cognitive performance over 24 hours for four groups: control, sleep-deprived (SD), SD + energy deficit, and SD + energy deficit + fluid restricted. Fatigue levels were quantified using the Profile of Mood States (POMS) survey. Linear mixed-effects (LME) models allowed for testing of group-specific differences in cognitive performance while accounting for subject-level variation. Starting fatigue levels were similar among all groups, while 24-hour fatigue levels differed significantly. For each cognitive performance test, results were modeled separately. The simplest LME model contained a significant fixed-effects term for slope and intercept. Moreover, the simplest LME model used a single slope coefficient to fit data from all four groups, suggesting that loss in cognitive performance over a 24-hour duty cycle with respect to fatigue level is similar regardless of the cause.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.040
GPT teacher head0.378
Teacher spread0.338 · 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 teacher head, not a consensus.

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

Citations14
Published2010
Admission routes1
Has abstractyes

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