Optical approach to the salivary pellicle
Bibliographic record
Abstract
The salivary pellicle plays an important role in oral physiology, yet noninvasive in situ characterization and mapping of this layer remains elusive. The goal of this study is to develop an optical approach for the real-time, noninvasive mapping and characterization of salivary pellicles using optical coherence tomography (OCT) and optical coherence microscopy (OCM). The long-term goals are to improve diagnostic capabilities in the oral cavity, gain a better understanding of physiological and pathological processes related to the oral hard tissues, and monitor treatment responses. A salivary pellicle is incubated on small enamel cubes using human whole saliva. OCT and OCM imaging occurs at 0, 10, 30, 60 min, and 24 h. For some imaging, spherical gold nanoparticles (15 nm) are added to determine whether this would increase the optical signal from the pellicle. Multiphoton microscopy (MPM) provides the baseline information. In the saliva-incubated samples, a surface signal from the developing pellicle is visible in OCT images. Pellicle "islands" form, which increase in complexity over time until they merge to form a continuous layer over the enamel surface. Noninvasive, in situ time-based pellicle formation on the enamel surface is visualized and characterized using optical imaging.
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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) | 0.001 | 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) | 0.001 | 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".