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Record W2127301534 · doi:10.3109/07420528.2012.675257

Photic Resetting in Night-Shift Work: Impact on Nurses' Sleep

2012· article· en· W2127301534 on OpenAlexafffundabout
Diane B. Boivin, Philippe Boudreau, Francine O. James, N.M.K. Ng Ying Kin

Bibliographic record

VenueChronobiology International · 2012
Typearticle
Languageen
FieldPsychology
TopicSleep and Work-Related Fatigue
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersCanadian Institutes of Health Research
KeywordsCircadian rhythmMorningMelatoninDaytimeSleep (system call)MedicineShift workDuskPsychologyAudiologyInternal medicinePsychiatryBiology

Abstract

fetched live from OpenAlex

The objective of this study was to quantify daytime sleep in night-shift workers with and without an intervention designed to recover the normal relationship between the endogenous circadian pacemaker and the sleep/wake cycle. Workers of the treatment group received intermittent exposure to full-spectrum bright light during night shifts and wore dark goggles during the morning commute home. All workers maintained stable 8-h daytime sleep/darkness schedules. The authors found that workers of the treatment group had daytime sleep episodes that lasted 7.1 ± .1 h (mean ± SEM) versus 6.6 ± .2 h for workers in the control group (p = .04). The increase in total sleep time co-occurred with a larger proportion of the melatonin secretory episode during daytime sleep in workers of the treatment group. The results of this study showed reestablishment of a phase angle that is comparable to that observed on a day-oriented schedule favors longer daytime sleep episodes in night-shift workers. (Author correspondence: diane.boivin@douglas.mcgill.ca ).

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 studies0.0000.000
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 head0.023
GPT teacher head0.358
Teacher spread0.335 · 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

Citations94
Published2012
Admission routes3
Has abstractyes

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