doi:10.1155/2012/672403 Research Article Normative Data for Bone Mass in Healthy Term Infants from Birth to 1 Year of Age
Bibliographic record
Abstract
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For over 2 decades, dual-energy X-ray absorptiometry (DXA) has been the gold standard for estimating bone mineral density (BMD) and facture risk in adults. More recently DXA has been used to evaluate BMD in pediatrics. However, BMD is usually assessed against reference data for which none currently exists in infancy. A prospective study was conducted to assess bone mass of term infants (37 to 42 weeks of gestation), weight appropriate for gestational age, and born to healthy mothers. The group consisted of 33 boys and 26 girls recruited from the Winnipeg Health Sciences Center (Manitoba, Canada). Whole body (WB) as well as regional sites of the lumbar spine (LS 1–4) and femur was measured using DXA (QDR 4500A, Hologic Inc.) providing bone mineral content (BMC) for all sites and BMD for spine. During the year, WB BMC increased by 200 % (76.0 ± 14.2 versus 227.0±29.7 g), spine BMC by 130 % (2.35±0.42 versus 5.37±1.02 g), and femur BMC by 190 % (2.94±0.54 versus 8.50±1.84 g). Spine BMD increased by 14 % (0.266 ± 0.044 versus 0.304 ± 0.044 g/cm2) during the year. This data, representing the accretion of bone mass during the first year of life, is based on a representative sample of infants and will aid in the interpretation of diagnostic DXA scans by researchers and health professionals. 1.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.227 | 0.201 |
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".