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Record W2137091640 · doi:10.1177/15648265020233s135

Contribution of Calcium and Other Dietary Components to Global Variations in Bone Mineral Density in Young Adults

2002· article· en· W2137091640 on OpenAlexaffabout
R. M. Parr, Abhijit Dey, Eugène McCloskey, Namık Aras, Á. Balogh, A Borelli, S. Krishnan, G. Lobo, Ling Qin, Y. Zhang, Selma Cvijetić, Vladimir Zaichick, M. Lim-Abraham, K. Bose, S. Wynchank, G. V. Iyengar

Bibliographic record

VenueFood and Nutrition Bulletin · 2002
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsBone mineralAnthropometryOsteoporosisFemoral neckMedicineEnvironmental healthLumbar spineAtomic energyDemographyGerontologyGeographyAgency (philosophy)SurgeryEndocrinologyInternal medicine

Abstract

fetched live from OpenAlex

A research project on comparative international studies of osteoporosis using isotope techniques was organized by the International Atomic Energy Agency (IAEA) with the participation of 12 countries (Brazil, Canada, Chile, China, Croatia, Hungary, Philippines, Russia, Singapore, South Africa, Turkey, and the United Kingdom). Participating centers in 11 countries (all but the UK) made measurements and collected data on men and women aged 15 to 49 years. In addition to studies of bone mineral density (BMD) at the femoral neck and lumbar spine using DEXA, anthropometric, lifestyle, and nutritional data were also collected. The results of the nutritional studies are reviewed in this paper. Overall, about 8% of the observed variability in spine BMD could be attributed to nutritional factors in men and women; in men, no such relationship could be determined. No single nutritional component (not even calcium) stood out as being of particular importance across all participating centers.

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)0.000
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 score0.014
Threshold uncertainty score0.280

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.028
GPT teacher head0.290
Teacher spread0.261 · 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

Citations18
Published2002
Admission routes2
Has abstractyes

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