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Record W2155374241 · doi:10.1016/j.jocd.2005.10.003

Effect of Diagnostic Radioisotopes and Radiographic Contrast Media on Measurements of Lumbar Spine Bone Mineral Density and Body Composition by Dual-Energy X-Ray Absorptiometry

2006· article· en· W2155374241 on OpenAlexafffund
Alessandra Sala, Colin E. Webber, Jacqueline Halton, Judy Morrison, Lesley Beaumont, Anna Zietak, Ronald D. Barr

Bibliographic record

VenueJournal of Clinical Densitometry · 2006
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsChildren's Hospital of Eastern OntarioHamilton Health SciencesMcMaster UniversityMcMaster Children's Hospital
FundersMcMaster UniversityAmerican Cancer Society
KeywordsMedicineNuclear medicineBone mineralDual-energy X-ray absorptiometryRadiographyRadiologyMagnetic resonance imagingLean body massDensitometryDual energyBone mineral contentBone densityOsteoporosisBody weightInternal medicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.029
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.353
Teacher spread0.331 · 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 source (direct Gemma or distilled Codex), 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

Citations27
Published2006
Admission routes2
Has abstractno

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