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Record W6943670401 · doi:10.17605/osf.io/shcwt

The Effects of the Light Necessary for Space Horticulture on Emotion, Cognition and Stress

2022· other· en· W6943670401 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Science Framework · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsAffect (linguistics)Vigilance (psychology)CognitionPsychomotor learningArousalDistressCoping (psychology)Space (punctuation)

Abstract

fetched live from OpenAlex

Space use horticulture systems are currently being developed and will be an important part in long duration space exploration. However, it is mostly unknown what effect exposure to these systems (specific LED lights and plants) will have on people. While exposure to nature is often associated with reduced stress, increased cognitive performance and positive emotion, research investigating LED lit environments has found effects vary depending on the lighting qualities (e.g., wavelength, intensity) among other factors. No published studies could be identified that investigate the effects of the light necessary to grow plants without sunlight. Therefore, utilizing a within-subjects design, this study will compare the short-term effects of sitting near two horticulture models: one with the light optimized for plant growth, the other, a normalized white light. Effects for emotional affect will be measured via the Positive and Negative Affect Schedule (PANAS), emotional arousal via the Subjective Units of Distress Scale (SUDS), cognition via the Psychomotor Vigilance Test (PVT), and indicators of stress (cognitive performance and heart rate variability) measured during the Montreal Stress Imaging Test (MIST). Implications will include guiding further research aimed at developing horticulture systems which optimize both plant growth and their effect on humans in space and comparable indoor environments on earth.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.154
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0030.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.290
Teacher spread0.281 · 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 designNot applicable
Domainnot available
GenreOther

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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