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Record W2111564267 · doi:10.1055/s-2006-934220

Magnetic Resonance Imaging of Joint Replacements

2006· review· en· W2111564267 on OpenAlexaff
Ali Naraghi, Lawrence M. White

Bibliographic record

VenueSeminars in Musculoskeletal Radiology · 2006
Typereview
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsUniversity Health NetworkMount Sinai Hospital
Fundersnot available
KeywordsMedicineMagnetic resonance imagingPeriprostheticArthroplastyRadiologyOrthopedic surgeryRadiographyJoint replacementRadiological weaponSurgery

Abstract

fetched live from OpenAlex

An increasing number of joint replacements are being performed annually. Complications of joint arthroplasty are diverse and may involve the hardware as well as osseous and soft tissue components. Although modalities such as conventional radiography and scintigraphy remain the mainstay of radiological investigation, in some cases these traditional methods of imaging may be negative or underestimate the extent of disease. Magnetic resonance imaging (MRI) has been considered of limited benefit following arthroplasty because of severe image degradation caused by metallic components. However, with modification of pulse sequences, artifact reduction and improved visualization of periprosthetic tissues are achievable, enabling a comprehensive assessment of articular and nonarticular pathologies. The common artifacts in the presence of orthopedic hardware, optimization of pulse sequences to minimize metal-related artifacts, and the clinical uses of MRI following joint replacement, particularly with regard to total hip arthroplasty, total knee arthroplasty, and shoulder arthroplasty, are reviewed.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.314
Teacher spread0.296 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations40
Published2006
Admission routes1
Has abstractyes

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