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Record W2992317162

Spatially resolved NMR relaxation of gas in cavitating liquid

2006· article· en· W2992317162 on OpenAlexafffundvenue
Igor V. Mastikhin, Benedict Newling

Bibliographic record

VenueCanadian acoustics · 2006
Typearticle
Languageen
FieldMaterials Science
TopicUltrasound and Cavitation Phenomena
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCuvetteCavitationFreonNuclear magnetic resonanceRelaxation (psychology)Saturation (graph theory)TransducerSIGNAL (programming language)ChemistryBubbleResonance (particle physics)Analytical Chemistry (journal)Materials scienceAtomic physicsMechanicsAcousticsOpticsPhysicsChromatography
DOInot available

Abstract

fetched live from OpenAlex

The nuclear magnetic resonance (NMR) relaxation parameters of Freon-22 gas in cavitating liquid, was investigated using magnetic resonance imaging (MRI). The behavior of gas in multibubble cavitation was analyzed using 2.35 T MRI scanner with 20 kHz Langevin type transducer at standing wave conditions inside the water-filled cuvette. The NMR relaxation parameter T2 was measured using CPMG sequences to obtain information about the amount of Freon in dissolved and free states before, during, and after cavitation. The signal intensity of the dissolved Freon was saturated by a short recovery delay (1s) to attenuate signal to 32% of its initial intensity. The saturation delay was incremented from 10ms to 1s. It was observed that amount of observable gas inside the cuvette was slightly above the noise level before the cavitation, while the amount of free gas increased after initiation of cavitation. Result shows that signal intensity increase due to the presence of larger gas bubble.

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: Empirical
Teacher disagreement score0.660
Threshold uncertainty score0.925

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 head0.008
GPT teacher head0.208
Teacher spread0.200 · 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

Citations0
Published2006
Admission routes3
Has abstractyes

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