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Record W4390830001 · doi:10.1002/9781119697473.ch62

Sleep and Diabetes

2024· other· en· W4390830001 on OpenAlexaff
Sonya S. Deschênes, Amy McInerney, Norbert Schmitz

Bibliographic record

Venuenot available
Typeother
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
Fundersnot available
KeywordsDiabetes mellitusSleep (system call)MedicineDepression (economics)ObesityDiabetes managementSleep disorderType 2 diabetesPsychiatryGerontologyInsomniaInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Sleep, a behavioural process that is influenced by circadian, neurohormonal, and homeostatic processes, is critical for optimal functioning and well-being. This chapter discusses common sleep problems and disorders, their relationship with diabetes and diabetes complications, and their associations with diabetes management. One of the ways in which sleep disturbance may be linked to diabetes outcomes is via less effective diabetes self-care behaviours, which are vital for diabetes management and prevention of complications. Diabetes healthcare professionals can screen for sleeping problems using brief questionnaires during routine care appointments. A clearer understanding of the role of obesity and depression in the sleep–diabetes relationship is warranted. Longitudinal studies using objective sleep assessments are needed to clarify the role of sleep in the development of diabetes complications and its interaction with behaviour and mental health comorbidities.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.002

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 head0.007
GPT teacher head0.264
Teacher spread0.256 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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