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Record W1544918876 · doi:10.1002/9781118467831.ch19

Alzheimer's Disease and the Mistiming of Behavior

2015· other· en· W1544918876 on OpenAlexaff
Roxanne Sterniczuk, Michael C. Antle

Bibliographic record

Venuenot available
Typeother
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsUniversity of CalgaryDalhousie University
Fundersnot available
KeywordsCircadian rhythmNeuropathologyMelatoninNeuroscienceDiseaseChronotypeDark therapyAlzheimer's diseaseInternal medicineEndocrinologyPsychologyMedicineBiology

Abstract

fetched live from OpenAlex

Changes to circadian rhythms in individuals with Alzheimer's disease (AD) are more pronounced than those observed in normal aging. Environmental conditions appear to play an important role in the severity of altered daytime and nighttime activity levels. Daytime activity levels are higher for AD patients housed at home rather than in an institution, providing evidence for an increase in circadian disruptions due to institutionalization. AD patients exhibit changes to various aspects of physiology that are under circadian control. The most prominent changes include altered sleep architecture, shifted core body temperature (CBT), and diminished melatonin secretion. Altered sleep-wake patterns may influence the expression of AD neuropathology. Transgenic mouse models of AD are most often chosen for understanding the effects of the disease on circadian rhythms. Both pharmacological and nonpharmacological approaches have been considered as modulators of the circadian timing system and potential treatments for circadian disruptions in AD.

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)0.000
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.045
GPT teacher head0.281
Teacher spread0.237 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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