Children Z-Score Comparability of Bone Mineral Density Reference Databases for
Bibliographic record
Abstract
Summary of the published pediatric Hologic DXA reference sources for LS and TB BMD with a minimumof 200 white children and adolescents First author(Ref.) Kalkwarf (17) Ward (18) Kelly (19) Ellis (20) a Bachrach(15) b,c Faulkner (16) Country, year USA, 2007 UK, 2007 USA, 2005 USA, 2001 USA, 1999 Canada, 1996Age range (yr) F, 7–16; M, 7–17 5–18 3–20 5–18 8.8–25.9 8–17No. of subjects(females/males)1554 (793/761) 435 (200/235) LS, 1444 (942/502);TB, 1948 (1088/860)982 (537/445) 423 (230/193) 234 (124/110)Hologic model;scan-modeQDR-4500A;QDR-4500W;Delphi-A; all FBQDR Discovery,FBQDR-4500A;Delphi-A; all FBQDR-2000W; PB QDR-1000W; PB QDR-2000; FBSoftware version 11.1 to 12.3(automatic lowbone densitydetection)12.1 (fast arraymode; LS,auto-lowdensityoption; TB,adult analysisalgorithm)12.1 (automaticlow densityanalysis)5.56 (bodycompositionsoftware)6.10 TB, 5.56A; LS,4.42AStudy design Prospective Prospective Prospective Prospective Prospective ProspectiveMulticenter study Yes (5 centers) No Yes (5 centers) No No No
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.044 | 0.013 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".