Highly depth-resolved chirped pulse photothermal radar for bone diagnostics
Bibliographic record
Abstract
A novel chirped pulse photothermal (PT) radiometric radar with improved sensitivity over the conventional harmonically modulated thermal-wave radar technique and alternative pulsed laser photothermal radiometry is introduced for the diagnosis of biological samples, especially bones with tissue and skin overlayers. The constraints imposed by the laser safety (maximum permissible exposure) ceiling on pump laser energy and the strong attenuation of thermal-wave signals in tissues significantly limit the photothermally active depth in most biological specimens to a level which is normally insufficient for practical applications (a few mm below the skin surface). A theoretical approach for improvement of signal-to-noise ratio (SNR), minimizing the static (dc) component of the photothermal signal and making use of the photothermal radiometric nonlinearity has been introduced and verified by comparing the SNR of four distinct excitation wave forms (sine-wave, square-wave, constant-width and constant duty-cycle pulses) for chirping the pump laser, under constant exposure energy. At low frequencies fixed-pulsewidth chirps of large peak power were found to be superior to all other equal-energy modalities, with an SNR improvement up to two orders of magnitude. Distinct thickness-dependent characteristic delay times in a goat bone were obtained, establishing an active depth resolution range of ~2.8 mm in a layered skin-fat-bone structure, a favorable result compared to the maximum reported pulsed photothermal radiometric depth resolution <1 mm in turbid biological media.
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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 | 0.001 | 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 | 0.000 |
| 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".