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Record W2026083078 · doi:10.1002/mrm.23074

Understanding quantitative pulsed CEST in the presence of MT

2011· article· en· W2026083078 on OpenAlexafffund
Kimberly L. Desmond, Greg J. Stanisz

Bibliographic record

VenueMagnetic Resonance in Medicine · 2011
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreUniversity of Toronto
FundersCanadian Institutes of Health ResearchOntario Institute for Cancer Research
KeywordsMagnetization transferChemistryMagnetizationImaging phantomNuclear magnetic resonanceBloch equationsSaturation (graph theory)Ammonium chlorideAnalytical Chemistry (journal)ProtonSpectral lineMagnetic fieldPhysicsPhysical chemistryChromatographyOpticsMagnetic resonance imaging

Abstract

fetched live from OpenAlex

Phantom experiments in agar and ammonium chloride were performed to evaluate a three-pool model of magnetization transfer and chemical exchange saturation transfer (CEST) in a pulsed saturation transfer experiment. The utility of the pulsed CEST method was demonstrated by varying the pH of the phantoms and observing the effect upon the CEST spectra both with and without the solid agar (the magnetization transfer pool), while fitting the spectra to the Bloch equation model with exchange. Pulsed CEST could be used to robustly quantify parameters related to CEST, including the exchange rate constant describing proton exchange with free water and the concentration of exchanging protons. Furthermore, the exchange rate constant and the CEST pool offset frequency of the ammonium chloride remained unchanged in the presence of a magnetization transfer pool. The logarithm of the fitted exchange rate constant was linearly related to pH: this relationship was maintained in the presence of magnetization transfer.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.240
GPT teacher head0.378
Teacher spread0.138 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations99
Published2011
Admission routes2
Has abstractyes

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