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Record W3033374523 · doi:10.1177/0748730420929448

Are Circadian Disturbances a Core Pathophysiological Component of Schizophrenia?

2020· review· en· W3033374523 on OpenAlexafffund
Tara C. Delorme, Lalit K. Srivastava, Nicolas Cermakian

Bibliographic record

VenueJournal of Biological Rhythms · 2020
Typereview
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaVelux Stiftung
KeywordsCircadian rhythmSchizophrenia (object-oriented programming)NeurosciencePsychologyChronobiologyPsychiatry

Abstract

fetched live from OpenAlex

Schizophrenia is a multifactorial disorder caused by a combination of genetic variations and exposure to environmental insults. Sleep and circadian rhythm disturbances are a prominent and ubiquitous feature of many psychiatric disorders, including schizophrenia. There is growing interest in uncovering the mechanistic link between schizophrenia and circadian rhythms, which may directly affect disorder outcomes. In this review, we explore the interaction between schizophrenia and circadian rhythms from 2 complementary angles. First, we review evidence that sleep and circadian rhythm disturbances constitute a fundamental component of schizophrenia, as supported by both human studies and animal models with genetic mutations related to schizophrenia. Second, we discuss the idea that circadian rhythm disruption interacts with existing risk factors for schizophrenia to promote schizophrenia-relevant behavioral and neurobiological abnormalities. Understanding the mechanistic link between schizophrenia and circadian rhythms will have implications for mitigating risk to the disorder and informing the development of circadian-based therapies.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.158
GPT teacher head0.335
Teacher spread0.177 · 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
GenreReview

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

Citations38
Published2020
Admission routes2
Has abstractyes

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