Dental diagnostic clinical instrument ("Canary") development using photothermal radiometry and modulated luminescence
Bibliographic record
Abstract
Since 1999, our group at the CADIFT, University of Toronto, has developed the application of Frequency Domain Photothermal Radiometry (PTR) and Luminescence (LUM) to dental caries detection. Various cases including artificial caries detection have been studied and some of the inherent advantages of the adaptation of this technique to dental diagnostics in conjunction with modulated luminescence as a dual-probe technique have been reported. Based on these studies, a portable, compact diagnostic instrument for dental clinic use has been designed, assembled and tested. A semiconductor laser, optical fibers, a thermoelectric cooled mid-IR detector, and a USB connected data acquisition card were used. Software lock-in amplifier techniques were developed to compute amplitude and phase of PTR and LUM signals. In order to achieve fast measurement and acceptable signal-to-noise ratio (SNR) for clinical application, swept sine waveforms were used. As a result sampling and stabilization time for each measurement point was reduced to a few seconds. A sophisticated software interface was designed to simultaneously record intra-oral camera images with PTR and LUM responses. Preliminary results using this instrument during clinical trials in a dental clinic showed this instrument could detect early caries both from PTR and LUM signals.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".