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Record W2597684773 · doi:10.1177/1078345817700163

Sleep Disorders and Therapeutic Management: A Survey in a French Population of Prisoners

2017· article· en· W2597684773 on OpenAlexaboutno aff
Anaïs Goudard, Laure Lalande, Camille Bertin, Marie Sautereau, Marc Le Borgne, Delphine Cabelguenne

Bibliographic record

VenueJournal of Correctional Health Care · 2017
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInsomniaPrisonPsychiatryHypnoticEtiologyRuminationQuarter (Canadian coin)PopulationSleep (system call)PsychologyCognition

Abstract

fetched live from OpenAlex

In a French prison, most inmates reported not being satisfied with their sleep. Life habits between good and bad sleepers were not significantly different except for television and smoking. The most frequently reported symptom of insomnia was several awakenings at night, and the most frequently cited etiologies were rumination of thoughts and noise. Most patients reported that their sleeping problems began or worsened after incarceration. A quarter of the inmates were following a hypnotic treatment, and most of these treatments began in prison. Only 42% of patients were satisfied with its effectiveness. These observations enabled us to make recommendations for healthy sleep patterns such as respecting normal night-and-day cycles, encouraging to stop smoking, and promoting appropriate use of hypnotic treatments.

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 score0.107
Threshold uncertainty score0.213

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.020
GPT teacher head0.347
Teacher spread0.327 · 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

Citations13
Published2017
Admission routes1
Has abstractyes

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