Photoacoustic and ultrasonic signatures of early bone density variations
Bibliographic record
Abstract
This study examines the application of backscattered ultrasound (US) and photoacoustics (PA) for assessment of bone structure and density variations. Both methods are applied in the frequency-domain, employing linear frequency modulation chirps. An 800-nm CW laser and a 3.5-MHz ultrasonic transducer are used for transmitting the signal. The backscattered pressure waves are detected with a 2.2-MHz US transducer. Experiments are focused on detection and evaluation of PA and US signals from in-vitro animal and human bones with cortical and trabecular sublayers. Osteoporotic changes in the bone are simulated by using a very mild demineralization solution (EDTA). Changes in the time-domain signal as well as integrated backscattering spectra are compared for each sample before and after demineralization. Results show the ability of US to generate detectable signals from deeper bone sublayers, whereas the PA signals show higher sensitivity to the variation in bone density. While US signal variation with changes in the cortical layer is insignificant, PA has proven to be able to detect minor variation of the cortical bone density.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".