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Record W3017184025 · doi:10.1177/0846537120919627

Bone Mineral Densitometry Reporting: Pearls and Pitfalls

2020· review· en· W3017184025 on OpenAlexaff
Patrick Martineau, Sarah Morgan, William D. Leslie

Bibliographic record

VenueCanadian Association of Radiologists Journal · 2020
Typereview
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineBone mineralDensitometryDual energyDual-energy X-ray absorptiometryClinical PracticeMedical physicsInterpretation (philosophy)RadiologyOsteoporosisPhysical therapyPathologyInternal medicineComputer science

Abstract

fetched live from OpenAlex

Dual-energy X-ray absorptiometry (DXA) is the method of choice for assessing bone mineral density (BMD). Unfortunately, the performance and interpretation of DXA can be challenging and errors are common. In fact, it has been reported that up to 90% of BMD reports contain at least 1 error. Errors can be the result of technique or interpretative in nature or both and can result in inappropriate diagnosis and management. In this article, we review the various types of pitfalls frequently encountered by physicians interpreting DXA studies. Being aware of these pitfalls will help readers recognize and avoid them when encountered in clinical practice.

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)0.003
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.856
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.071
GPT teacher head0.383
Teacher spread0.312 · 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 designNot applicable
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

Citations26
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Association of Radiologists JournalSame topicBone health and osteoporosis researchFrench-language works237,207