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Prospective Memory and Sleep Quality

2023· article· en· W4387939385 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLecture Notes in Education Psychology and Public Media · 2023
Typearticle
Languageen
FieldPsychology
TopicCognitive Functions and Memory
Canadian institutionsBrock University
Fundersnot available
KeywordsProspective memoryProspective cohort studySleep (system call)PsychologyMedicineCognitionPsychiatryComputer scienceInternal medicine

Abstract

fetched live from OpenAlex

Sleep is a state in which the human mind and body are rested, while prospective memory helps humans remember future tasks or plan future events.[1] This study used the Comprehensive Assessment of Prospective Memory (CAPM) and the Sleep Quality Questionnaire (PSQI) to assess whether sleep quality affects prospective memory performance. The results showed that participants with PSQI scores between 6 and 21 had significantly lower CAPM scores than those between 0 and 5. Therefore this paper shows poor sleep quality, as measured by PSQI scores, was associated with a higher frequency of prospective memory failure. This result suggests better sleep quality is associated with better performance in prospective memory. Prospective memory is crucial to our daily life, and loss of prospective memory can have dire consequences. For example, people with diabetes forget to take their daily insulin injections. That’s why research on prospective memory is essential.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.752
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.389
Teacher spread0.348 · 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