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Record W2907493228 · doi:10.1109/tbme.2018.2890055

Time-Varying Respiratory Mechanics as a Novel Mechanism Behind Frequency Dependence of Impedance: A Modeling Approach

2018· article· en· W2907493228 on OpenAlexafffund
Hamed Hanafi Alamdari, Kamal El‐Sankary, Geoffrey N. Maksym

Bibliographic record

VenueIEEE Transactions on Biomedical Engineering · 2018
Typearticle
Languageen
FieldMedicine
TopicInhalation and Respiratory Drug Delivery
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTime domainRespiratory physiologyFrequency domainReactanceElastanceRespiratory systemElectrical impedanceMathematicsMechanicsStatistical physicsControl theory (sociology)PhysicsMathematical analysisComputer scienceMedicineVoltageArtificial intelligenceInternal medicine

Abstract

fetched live from OpenAlex

Frequency dependence of respiratory mechanics is a well-established behavior of the respiratory system and is known to be an indicator of severity of obstructive disease, attributed to both tissue viscoelasticity and heterogeneity of airflow in the lung. Despite the fact that respiratory parameters are known to vary in time, often amplified in disease, all analysis methods assume stationarity or short-time stationarity in the parameters used to describe the respiratory system, and the effects of this assumption have not yet been examined in any detail. Here, using a generalized approach, we developed a theory for time-varying respiratory mechanics in time-frequency domain for analysis of linear time-varying systems, then, we analyzed the same respiratory system model with time-varying parameters in the time domain. Both time-frequency domain and time-domain derivations revealed a striking correlation between time-varying behavior of the respiratory system and frequency dependence of resistance. Remarkably, this phenomenon arose from the amplitude of time variations of the elastance. This links two mechanisms that are known to increase in obstructive disease: apparent low frequency increases in resistance and the time variations of reactance.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.902
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.022
GPT teacher head0.255
Teacher spread0.233 · 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

Citations12
Published2018
Admission routes2
Has abstractyes

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