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Record W1500261210

Magnetic resonance imaging of acoustic streaming in gases

2006· article· en· W1500261210 on OpenAlexaffvenue
Benedict Newling, Duncan A. MacLean, Igor V. Mastikhin

Bibliographic record

VenueCanadian acoustics · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsPulse sequenceAmplitudeAcousticsPulse (music)Magnetic resonance imagingMagnetic fieldAcoustic streamingNuclear magnetic resonancePhysicsDisplacement (psychology)Optoacoustic imagingOpticsMaterials science
DOInot available

Abstract

fetched live from OpenAlex

A study was conducted to demonstrate the utility of magnetic resonance imaging (MRI) method for acoustic streaming (AS) in gases. The method used diverse array of possible image contrasts, which were manipulated through careful control of the spin physics during image acquisition to study the phenomenon of AS in gases. The position and velocity sensitization were performed through the use of magnetic field gradients and the pulse sequence timing diagram schematized the sequence of sample manipulation during the measurement. The imaging sequence was applied at 2.4 T to a 2m-long and 20-cm-diameter cylindrical tube filled with propane gas. The first data set showed 15 profiles, each acquired with a different amplitude of motion-sensitizing pulse-field-gradient (PFG) method. These measurements were repeated five times at 15-minutes intervals before, during, and after the establishment of an acoustic standing wave at 835 Hz in the tube.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score0.889

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 head0.004
GPT teacher head0.199
Teacher spread0.194 · 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

Citations1
Published2006
Admission routes2
Has abstractyes

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