MétaCan
Menu
Back to cohort
Record W2614819029 · doi:10.21037/atm.2017.04.27

CBT-I and the short sleep duration insomnia phenotype: a comment on Bathgate, Edinger and Krystal

2017· letter· en· W2614819029 on OpenAlexafffund
Célyne Bastien, Jason Ellis, Michael A. Grandner

Bibliographic record

VenueAnnals of Translational Medicine · 2017
Typeletter
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsUniversité Laval
FundersNational Heart, Lung, and Blood InstituteCanadian Institutes of Health Research
KeywordsInsomniaDepression (economics)PhenotypeSleep (system call)MedicineChronic insomniaPsychologyDuration (music)Clinical psychologyPsychiatryNeuroscienceSleep disorderBiologyGenetics

Abstract

fetched live from OpenAlex

Although the DSM-5 and the ICSD-3 do not discriminate among insomnia types or subtypes anymore, it appears that some specific insomnia phenotypes remain important to study. One of them is the object of the present paper: insomnia with short sleep duration. Since Vgontzas and colleagues (1) put forward a heuristic model of two insomnia phenotypes based on objective sleep duration, they have suggested that insomnia with short sleep duration is the most severe biological phenotype of insomnia, and research in this area has been blooming. The Penn State group has studied the impact of this phenotype on adolescents and its association with depression risks and inflammation (2-4). A recent review by Fernandez-Mandoza (5) also suggested that besides increased physiological hyperarousal and cardiometabolic and neuropsychiatric risks, insomnia with short sleep duration may even respond differently to treatment compared to other insomnia phenotypes.

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)0.006
metaresearch head score (Gemma)0.027
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.042
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0030.006
Open science0.0040.002
Research integrity0.0420.057
Insufficient payload (model declined to judge)0.0040.006

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 head0.057
GPT teacher head0.343
Teacher spread0.286 · 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
GenreCommentary

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

Citations4
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueAnnals of Translational MedicineSame topicSleep and related disordersFrench-language works237,207