MétaCan
Menu
Back to cohort
Record W2014935556 · doi:10.1002/mrm.21754

Susceptibility weighted imaging at ultra high magnetic field strengths: Theoretical considerations and experimental results

2008· article· en· W2014935556 on OpenAlex

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.

Bibliographic record

VenueMagnetic Resonance in Medicine · 2008
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of British Columbia Hospital
Fundersnot available
KeywordsVoxelImaging phantomSusceptibility weighted imagingSensitivity (control systems)Nuclear magnetic resonancePhase (matter)Specific absorption rateContrast (vision)VisibilityMaterials scienceMagnetic resonance imagingPhysicsOpticsComputer scienceArtificial intelligenceRadiologyMedicine

Abstract

fetched live from OpenAlex

We present numerical simulations and experimental results for susceptibility weighted imaging (SWI) at 7 T. Magnitude, phase, and SWI contrast were simulated for different voxel geometries and imaging parameters, resulting in an echo time of 14 msec for optimum contrast between veins and surrounding tissue. Slice thickness of twice the in-plane voxel size or more resulted in optimum vessel visibility. Phantom and in vivo data are in very good agreement with the simulations and the delineation of vessels at 7 T was superior compared to lower field strengths. The phase of the complex data reveals anatomical details that are complementary to the corresponding magnitude images. Susceptibility weighted imaging at very high field strengths is a promising technique because of its high sensitivity to tissue susceptibility, its low specific absorption rate, and the phase's negligible sensitivity to B(1) inhomogeneities.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.430
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.305
Teacher spread0.292 · 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