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Record W1968434513 · doi:10.1080/02841850601129015

The influence of magnetic resonance imaging findings of degenerative disease on dual-energy X-ray absorptiometry measurements in middle-aged men

2007· article· en· W1968434513 on OpenAlexaff
O. S. Donescu, Michele C. Battié, Tapio Videman

Bibliographic record

VenueActa Radiologica · 2007
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineMagnetic resonance imagingSagittal planeBone mineralLumbarFemoral neckNuclear medicineRadiologyDual-energy X-ray absorptiometryLumbar spineAnatomyOsteoporosisPathologySurgery

Abstract

fetched live from OpenAlex

PURPOSE: To examine degenerative features based on magnetic resonance imaging (MRI) measurements at the lumbar spine in relation to dual-energy X-ray absorptiometry (DXA), and to investigate whether bone mineral density (BMD) is reflected in the substitution of bone trabecular structure by fat at the vertebral body level indicated by MRI T1 relaxation time, endplate concavity, and hypertrophic (osteophytes and endplate sclerosis) MRI findings. MATERIAL AND METHODS: The sample for this cross-sectional study was composed of 102 subjects, 35-70 years old, from a population-based cohort. Data collection included DXA in the anterior-posterior projection at the L1-L4 vertebrae and right femoral neck, and MRI of the lumbar spine in the midsagittal plane. RESULTS: Age, vertebral signal intensity, osteophytes, and endplate concavity collectively explained 20% of the variance in spine BMD. CONCLUSION: The study findings suggest that degenerative findings based on MRI measurements at the lumbar spine have an influence on bone assessment using DXA. Therefore, an overall bone assessment such as DXA might not offer an accurate measure of BMD.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.198
Threshold uncertainty score0.374

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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 head0.040
GPT teacher head0.307
Teacher spread0.267 · 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

Citations11
Published2007
Admission routes1
Has abstractyes

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