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Record W7133088548

Enhancing Cognition by using Low-cost In-home Portable Sleep Equipment: A Feasibility Study

2019· dissertation· W7133088548 on OpenAlexafffund
David Robert Colelli

Bibliographic record

VenueTSpace · 2019
Typedissertation
Language
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsUniversity of Toronto
FundersUniversity of Toronto
KeywordsPolysomnographyObstructive sleep apneaSleep (system call)Sleep apneaCognitionBreathingGold standard (test)
DOInot available

Abstract

fetched live from OpenAlex

Obstructive sleep apnea (OSA), which causes pauses in breathing during sleep, increases the risk of developing cognitive impairment. In-laboratory polysomnography (iPSG) is the gold standard to diagnose OSA, but few patients are screened by iPSG due to refusal to spend a night in a sleep laboratory. Home sleep apnea testing (HSAT) may be a more accessible alternative, as it is simple to use, conveniently administered in a patient’s own home, and validated against iPSG. This study investigated the feasibility and practicality of using HSAT in cognitively impaired clinic patients and assessed the prevalence and factors associated with OSA. HSAT was found to be feasible and practical to assess for OSA. OSA was also prevalent in this population. As OSA is a modifiable risk factor for patients with cognitive impairment, HSAT has the potential to lead to expedited treatment for OSA, which may potentially improve health-related outcomes such as cognition.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
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 head0.043
GPT teacher head0.396
Teacher spread0.354 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2019
Admission routes2
Has abstractyes

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