The predictive role of bone turnover markers for BMD in middle-aged men
Bibliographic record
Abstract
Measurement of bone turnover markers has been proposed as a potentially valuable clinical laboratory aid in osteoporosis risk assessment. These markers may allow quantitative evaluation of rates of bone loss, and thereby identify persons at risk for osteoporosis at an earlier stage. As far as we know, this is the longest longitudinal study on bone turnover markers conducted in adult men. The objectives of this study were to determine whether markers of bone formation (type I procollagen amino-terminal propeptide, PINP, and carboxy-terminal propeptide, PICP), and of bone resorption (type I collagen carboxy-terminal telopeptide, ICTP), are predictive of changes in lumbar spine and femoral neck BMD over a 5-year period, and to determine the ability of the bone resorption marker urine amino-terminal telopeptide (NTx) to explain the variance in BMD change over the past 5 years in a group of men 35-69 years old. In this group, NTx was the only marker to correlate significantly with BMD changes at the femoral neck (r = -0.21), but not at the spine. The use of the biochemical markers studied to predict change in bone density in adult men in middle-aged years is of very limited value.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".