Diffuse reflectance spectroscopy in Barrett’s Esophagus: developing a large field‐of‐view screening method discriminating dysplasia from metaplasia
Bibliographic record
Abstract
We evaluated diffuse reflectance spectroscopy implemented as a small field-of-view technique for discrimination of dysplasia from metaplasia in Barrett's esophagus as an adjuvant to autofluorescence endoscopy. Using linear discriminant analysis on 2579 spectra measured in 54 patients identified an optimum a 4-wavelength classifier (at 485, 513, 598 and 629 nm). Sensitivity and specificity for a test data set were 0.67 and 0.85, respectively. Spectroscopic results show that this technique could be implemented in wide-field imaging mode to improve the accuracy of existing endoscopy techniques for finding early pre-malignant lesions in Barrett's esophagus. Results show that the discrimination occurs likely due to redistribution of blood content in the tissue sensed by the optical probing with the wavelength-dependent sampling depth.
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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 | 0.001 | 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 | 0.000 | 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 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".