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Record W1967295801 · doi:10.1002/mrm.10701

Regional variations in normal brain shown by quantitative magnetization transfer imaging

2004· article· en· W1967295801 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 · 2004
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsMagnetization transferWhite matterVoxelNuclear magnetic resonanceMagnetizationMagnetic resonance imagingNuclear medicinePhysicsMedicineRadiologyMagnetic field

Abstract

fetched live from OpenAlex

A quantitative magnetization transfer imaging (qMTI) study, based on a two-pool model of magnetization transfer, was performed on seven normal subjects to determine, on a regional basis, normal values for the pool sizes, exchange, and relaxation parameters that characterize the MT phenomenon. Regions were identified on high-resolution anatomical scans using a combination of manual and automatic methods. Only voxels identified as pure tissue at the resolution of the quantitative scans were considered for analysis. While no left/right differences were observed, significant differences were found among white-matter regions and gray-matter regions. These regional differences were compared with existing cytoarchitectural data. In addition, the pattern and magnitude of the regional differences observed in white matter was found to be different from that reported previously for an alternative putative MRI measure of myelination, the 10-50-ms T2 component described as myelin water.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.802
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.018
GPT teacher head0.319
Teacher spread0.300 · 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