A Clinical Evaluation of Vibration Testing in the Assessment of Osteoporosis
Bibliographic record
Abstract
Abstract Bone fracture is one of the most common medical problems which reduces the quality of life of individuals. In the United States, osteoporosis alone causes 1.3 million bone fractures a year, with an annual cost of $5.2 billion dollars. Osteoporosis is a disease in which low bone mass and changes in bone quality and architecture increase the risk of fractures. Women are at greater risk of developing osteoporosis than men. Osteoporosis targets both trabecular and cortical bone (Kanis et al., 1994; Kasra and Grynpas, 1994). Therefore, bone density of cortical bone structures such as ulna and mid-radius may be used as a predictor of osteoporotic fractures (Cummings et al., 1993). Bone quality assessment and predicting the risk of bone fracture is very important in prevention of fracture and proper bone treatment. In the NIH Consensus Development Statement (1984), the need for improved measurement techniques is emphasized.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".