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Record W4233741447 · doi:10.1002/mrm.1167

Chemical shift imaging with spectrum modeling

2001· article· en· W4233741447 on OpenAlexaff
Li An, Qing‐San Xiang

Bibliographic record

VenueMagnetic Resonance in Medicine · 2001
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNuclear magnetic resonanceImaging phantomAmplitudeChemical shiftSpin echoNuclear magnetic resonance spectroscopyNonlinear systemMaterials scienceMagnetic resonance imagingPhysicsChemistryComputational physicsOptics

Abstract

fetched live from OpenAlex

A new chemical shift imaging technique was developed to efficiently obtain separate images for multiple chemical shift peaks from a set of spin-echo acquisitions. Information from localized NMR spectroscopy was used to model the chemical shift spectrum as sharp peaks with known resonance frequencies but unknown amplitudes. Based on this model, a set of spin-echo images with shifted 180 degrees RF pulses were acquired, in which the magnetization vectors of different chemical components were put into different directions. The amplitudes of the chemical shift peaks were obtained by solving nonlinear equations in a region-growing process. Experimental results on an ethanol phantom as well as a subject with silicone breast implants are presented. Magn Reson Med 46:126-130, 2001.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.751
Threshold uncertainty score0.476

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 head0.016
GPT teacher head0.300
Teacher spread0.284 · 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 designOther design
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

Citations35
Published2001
Admission routes1
Has abstractyes

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