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Record W2176602456 · doi:10.1152/advances.2001.25.2.29

SLEEP AS A TEACHING TOOL FOR INTEGRATING RESPIRATORY PHYSIOLOGY AND MOTOR CONTROL

2001· review· en· W2176602456 on OpenAlexaff
Stephen R. Thompson, Uwe Ackermann, Richard L. Horner

Bibliographic record

VenueAJP Advances in Physiology Education · 2001
Typereview
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSleep (system call)Respiratory physiologyCurriculumControl (management)NeuroscienceWakefulnessHuman physiologyPhysiologyCognitive sciencePsychologyComputer scienceMedicineRespiratory systemArtificial intelligencePsychiatry

Abstract

fetched live from OpenAlex

Sleep exerts major effects on most fundamental homeostatic mechanisms. Current data suggest, however, that students of physiology and medicine typically receive little or no formal teaching in sleep. Because sleep takes up a significant component of our life span, it is proposed that current teaching in systems and integrative physiology is not representative if it is confined to functions describing wakefulness only. We propose that sleep can be readily integrated into various components of physiology and medical curricula simply by emphasizing how commonly taught physiological processes are importantly affected by sleep mechanisms. In our experience, this approach can be used to reinforce basic physiological principles while simultaneously introducing sleep physiology into the students' training. We find that students have a general and inherent interest in sleep and related clinical disorders, and this proves useful as an effective means to teach the material. In this paper, examples of how sleep influences motor control and the respiratory system will illustrate these points. These considerations also highlight some important gaps in traditional teaching of respiratory physiology.

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)0.004
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 score0.993
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.035
GPT teacher head0.389
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 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

Citations21
Published2001
Admission routes1
Has abstractyes

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