Combined photoacoustic and ultrasonic diagnosis of early bone loss and density variations
Bibliographic record
Abstract
Over the past two decades, osteoporosis has been recognized among the most serious public health problems. Fortunately with the growing awareness of osteoporosis, new treatments have been developed for the prevention of fracture. At the same time, there is a rapid improvement in diagnostic methods. In this study biomedical photoacoustics (PA) is applied to the analysis of bone mineral concentration. The PA signal depends on optical as well as mechanical properties of the object and therefore has the potential to provide higher sensitivity to density variations compared with standard diagnostic methods, like ultrasound. A laser source with 800 nm wavelength and different ultrasonic transducers with resonance frequencies in the range 1 to 5 MHz were employed. The CW or frequency-domain (FD) PA radar method was utilized with linear frequency modulation chirps to provide temporal gating control over the transmitted signal and higher sensitivity in the detected signal. The laser intensity was set below the safety standards for skin exposure. The preliminary studies showed adequate optical absorption by cortical bone to generate measurable PA signals and the transmission of laser light through this layer. Experiments are focused on detection and evaluation of PA signals from in-vitro animal cortical bones with and without a trabecular sublayer. The trabecular layer is then diluted by chemical etching and differences in the PA signals are discussed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".