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Record W2097859795 · doi:10.1002/jmri.1174

Oblique sagittal view of the anterior cruciate ligament: Comparison of coronal vs. axial planes as localizing sequences

2001· article· en· W2097859795 on OpenAlexaff
John E. Barberie, B W Carson, Martin Finnegan, Anthony Wong

Bibliographic record

VenueJournal of Magnetic Resonance Imaging · 2001
Typearticle
Languageen
FieldMedicine
TopicCardiac tumors and thrombi
Canadian institutionsSt. Paul's Hospital
Fundersnot available
KeywordsCoronal planeSagittal planeOblique caseMedicineAnterior cruciate ligamentAxial symmetryAnatomyOrthodonticsNuclear medicineMathematicsGeometry

Abstract

fetched live from OpenAlex

The purpose of this study was to determine whether oblique sagittal T2-weighted images of the anterior cruciate ligament (ACL) are better prescribed off axial or coronal localizing images. Thirty-one patients underwent two sets of oblique sagittal T2-weighted fast spin-echo sequences to evaluate the ACL. One oblique was prescribed from a coronal localizing sequence, while the other was prescribed off an axial series. Objective (average number of images to demonstrate ACL) and subjective (radiologist's confidence level) evaluations of both sequences were performed independently of the other and then comparatively by two radiologists. The coronally prescribed sagittal oblique was subjectively preferred in 18 patients, the axially prescribed oblique was preferred in one patient, and both sequences were felt to be equivalent in 12 patients. In 13 intact ligaments, the average number of images clearly demonstrating the entire length of the ACL was 1.77 on the coronally prescribed sequence and 1.31 on the axially prescribed images. Oblique sagittal images prescribed off a coronal localizer are both subjectively and objectively more effective than axially prescribed sagittal obliques in evaluating the ACL.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score0.448

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.014
GPT teacher head0.297
Teacher spread0.283 · 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 designObservational
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

Citations24
Published2001
Admission routes1
Has abstractyes

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