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Record W2228496000 · doi:10.1152/jappl.2000.89.2.413

A new ventilator for monitoring lung mechanics in small animals

2000· article· en· W2228496000 on OpenAlexaff
G. Volgyesi, Lorraine N. Tremblay, Peter M. Webster, Noé Zamel, Arthur S. Slutsky

Bibliographic record

VenueJournal of Applied Physiology · 2000
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsRespiratory physiologyLungMedicineIntensive care medicineMechanicsCardiologyInternal medicinePhysics

Abstract

fetched live from OpenAlex

Researchers investigating the genetic component of various disease states rely increasingly on murine models. We have developed a ventilator to simplify respiratory research in small animals down to murine size. The new ventilator provides constant-flow inflation and tidal volume delivery independent of respiratory parameter changes. The inclusion of end-inspiratory and end-expiratory pauses simplifies the measurement of airway resistance and compliance and allows the detection of dynamic hyperinflation (auto-positive end-expiratory pressure). After bench testing, we performed intravenous methacholine challenge on two strains of mice (A/J and C57bl/bj) known to differ in their responses by using the new ventilator. Dynamic hyperinflation and a decrease in compliance developed during methacholine challenge whenever respiratory rates of 60-120 breaths/min were employed. In contrast, if dynamic hyperinflation was prevented by lengthening expiratory time, (respiratory rate = 20 breaths/min), static compliance remained constant. More importantly, the coefficient of variation of the results decreased when lung volume shifts were prevented. In conclusion, airway challenge studies have greater precision when dynamic hyperinflation is prevented.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.404

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 head0.022
GPT teacher head0.285
Teacher spread0.263 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations40
Published2000
Admission routes1
Has abstractyes

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