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Record W2139549280 · doi:10.1088/0967-3334/33/3/487

Intraluminal ultrasonic probe for volumetric monitoring of liquid gastroesophageal reflux

2012· article· en· W2139549280 on OpenAlexaff
Xuexin Gao, Daniel Sadowski, Martin P. Mintchev

Bibliographic record

VenuePhysiological Measurement · 2012
Typearticle
Languageen
FieldMedicine
TopicGastroesophageal reflux and treatments
Canadian institutionsUniversity of AlbertaUniversity of Calgary
FundersCentre National de la Recherche ScientifiqueCentre National d’Etudes SpatialesAgence Nationale de la Recherche
KeywordsUltrasonic sensorBiomedical engineeringMaterials scienceUltrasoundRefluxCatheterVolume (thermodynamics)RadiologyMedicinePathology

Abstract

fetched live from OpenAlex

Methods for volumetric monitoring of liquid gastroesophageal reflux (GER) are still lacking. The aim of this study was to develop an automated intraluminal measurement technique which allows ambulatory volumetric quantification of liquid GER utilizing a minimum-cost intraluminal ultrasonic probe. This probe consists of two 2 MHz ultrasonic crystals longitudinally assembled along a multi-channel intraluminal impedance (MII) catheter. The proposed probe was initially tested with tubular phantoms of different diameters. Measurements of the cross-sectional areas of the phantoms showed high correlation with the actual areas (R(2) = 0.99). Subsequently, two in-vivo human tests were performed. For each human test the catheter assembly was inserted transnasally and the ultrasonic probe was placed in the area of the lower esophageal sphincter. Multiple liquid swallows of different volumes were invoked using electrolyte drinks. Sectional luminal volume (SLV) in the esophagus between the two ultrasonic crystals was obtained. Results of the swallows demonstrated that measured SLVs correlated with the actual swallowed liquid volume. The ultrasonic probe was combined with a MII catheter to discriminate between antegrade and retrograde bolus transit. Increases of SLVs during liquid GER episodes could be utilized to evaluate GER volume in the vicinity of the ultrasonic probe.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.413
Threshold uncertainty score0.683

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.116
GPT teacher head0.328
Teacher spread0.212 · 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 designObservational
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

Citations4
Published2012
Admission routes1
Has abstractyes

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