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Record W2024128814 · doi:10.1002/mrm.10467

Optimized spiral imaging for measurement of myocardial <i>T</i><sub>2</sub> relaxation

2003· article· en· W2024128814 on OpenAlex
Warren D. Foltz, Osama Sam Al-Kwifi, Marshall S. Sussman, Jeff A Stainsby, Graham A. Wright

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMagnetic Resonance in Medicine · 2003
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
FundersHeart and Stroke Foundation of Canada
KeywordsStandard deviationSpiral (railway)Relaxation (psychology)ResidualMicrocirculationGold standard (test)Nuclear magnetic resonanceBiomedical engineeringMathematicsComputer sciencePhysicsNuclear medicineMedicineStatisticsAlgorithmMathematical analysisRadiologyInternal medicine

Abstract

fetched live from OpenAlex

Microcirculation oxygen levels and blood volumes should be reflected in measurements of myocardial T(2) relaxation. This work describes the optimization of a spiral imaging strategy for robust myocardial T(2) measurement to minimize the standard deviation of T(2) measurement (sigmaT(2)). Theoretical and experimental studies of blurring at muscle/blood interfaces enabled the derivation of parameter sets which reduce sigma T(2) to the level of 5%. T(2) relaxation mapping within healthy volunteers provided estimation of residual sigmaT(2) within the optimized technique. The standard deviation in T(2) measurement across regions of interest (ROIs) in different locations is about 9%. The standard deviation in T(2) measurement in an ROI across different time points is about 5%.

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.

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)0.001
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: none
Teacher disagreement score0.673
Threshold uncertainty score0.547

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.024
GPT teacher head0.292
Teacher spread0.268 · 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