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Ventilation and Respiratory Mechanics

2012· article· en· W4409120939 on OpenAlex
A. William Sheel, Lee M. Romer

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

VenueComprehensive physiology · 2012
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRespiratory physiologyVentilation (architecture)Respiratory systemMedicineMechanicsIntensive care medicinePhysicsInternal medicineThermodynamics

Abstract

fetched live from OpenAlex

Abstract During dynamic exercise, the healthy pulmonary system faces several major challenges, including decreases in mixed venous oxygen content and increases in mixed venous carbon dioxide. As such, the ventilatory demand is increased, while the rising cardiac output means that blood will have considerably less time in the pulmonary capillaries to accomplish gas exchange. Blood gas homeostasis must be accomplished by precise regulation of alveolar ventilation via medullary neural networks and sensory reflex mechanisms. It is equally important that cardiovascular and pulmonary system responses to exercise be precisely matched to the increase in metabolic requirements, and that the substantial gas transport needs of both respiratory and locomotor muscles be considered. Our article addresses each of these topics with emphasis on the healthy, young adult exercising in normoxia. We review recent evidence concerning how exercise hyperpnea influences sympathetic vasoconstrictor outflow and the effect this might have on the ability to perform muscular work. We also review sex‐based differences in lung mechanics. © 2012 American Physiological Society. Compr Physiol 2:1093‐1142, 2012.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.900
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

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

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 head0.059
GPT teacher head0.311
Teacher spread0.253 · 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