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Record W2955016160 · doi:10.3390/ijerph16132336

Circadian Rhythms and Measures of CNS/Autonomic Interaction

2019· review· en· W2955016160 on OpenAlexaff
Francesco Riganello, Valeria Prada, Andrea Soddu, Carol Di Perri, Walter G. Sannita

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2019
Typereview
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsWestern University
Fundersnot available
KeywordsCircadian rhythmNeuroscienceAutonomic functionWakefulnessPsychologyAutonomic nervous systemBiologyHeart rate variabilityHeart rateElectroencephalographyEndocrinology

Abstract

fetched live from OpenAlex

The physiological role and relevance of the mechanisms sustaining circadian rhythms have been acknowledged. Abnormalities of the circadian and/or sleep-wakefulness cycles can result in major metabolic disorders or behavioral/professional inadequacies and stand as independent risk factors for metabolic, psychiatric, and cerebrovascular disorders and early markers of disease. Neuroimaging and clinical evidence have documented functional interactions between autonomic (ANS) and CNS structures that are described by a concept model (Central Autonomic Network) based on the brain-heart two-way interplay. The circadian rhythms of autonomic function, ANS-mediated processes, and ANS/CNS interaction appear to be sources of variability adding to a variety of environmental factors, and may become crucial when considering the ANS major role in internal environment constancy and adaptation that are fundamental to homeostasis. The CNS/ANS interaction has not yet obtained full attention and systematic investigation remains overdue.

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)0.003
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: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.232
GPT teacher head0.445
Teacher spread0.213 · 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
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

Citations74
Published2019
Admission routes1
Has abstractyes

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