Direct fluorescence visualization of clinically occult high‐risk oral premalignant disease using a simple hand‐held device
Bibliographic record
Abstract
BACKGROUND: A considerable proportion of oral cancer and precancer is not clinically apparent and could contribute significantly to the late diagnosis and high mortality of oral cancer. A simple method to identify such occult change is needed. METHODS: Patients in the Oral Dysplasia Clinics at British Columbia are currently being examined with a simple hand-held device that permits the direct visualization of alterations to autofluorescence in the oral cavity. Tissue showing loss of autofluorescence is biopsied. RESULTS: We present 3 representative cases in which occult lesions were identified with fluorescence visualization during longitudinal follow-up, resulting in the diagnosis of a primary dysplasia in case 1, a second primary cancer in case 2, and cancer recurrence in case 3. CONCLUSIONS: This is the first report of the diagnosis of occult oral disease using a simple noninvasive device. These early examples indicate the potential value of this technology to guide the management of patients with oral lesions, facilitating the detection of high-risk changes not apparent with white-light visualization.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".