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VALUE OF FAT SUPPRESSION IN GADOLINIUM‐ENHANCED MAGNETIC RESONANCE NEUROIMAGING

2011· article· en· W1924673616 on OpenAlexaff
Marc‐André d’Anjou, Éric Norman Carmel, Amy S. Tidwell

Bibliographic record

VenueVeterinary Radiology & Ultrasound · 2011
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsCegep de Saint HyacintheUniversité de Montréal
Fundersnot available
KeywordsGadoliniumMedicineMagnetic resonance imagingAdipose tissueSpinal cordNeuroimagingNervous systemCentral nervous systemPathologyNuclear magnetic resonanceRadiologyInternal medicine

Abstract

fetched live from OpenAlex

T1-weighted, gadolinium-enhanced magnetic resonance imaging is frequently used to investigate neurologic disease in small animals; however, the abundance of hyperintense adipose tissue adjacent to neural structures, particularly the cranial nerves and spinal cord, can decrease the conspicuity of contrast-enhanced tissues on T1-weighted images. For this reason, chemical fat saturation techniques are used to suppress the signal of adipose tissues, enabling improved depiction of gadolinium-enhanced structures and detection of lesions affecting the nervous system.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.776
Threshold uncertainty score0.588

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 head0.039
GPT teacher head0.314
Teacher spread0.275 · 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 designBench or experimental
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

Citations26
Published2011
Admission routes1
Has abstractyes

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