Bibliographic record
Abstract
Oral cancer is a complex disease that is characterized by histologic and genetic heterogeneity. The evolution and progression of this disease is thought to result from the accumulation of alterations in molecular pathways. Although the oral cavity is accessible for routine screening of suspicious lesions, gene alterations are known to accrue in histologically normal tissues. Therefore, some cancer forerunners may remain undetected clinically or histologically. Recently emerging optical and molecular technologies have provided a powerful means for redefining the extent of the field of alteration. Often this means expanding upon regions detectable with standard white light approaches. In this report, we used a newly developed optical technique, direct fluorescence visualization, to define a contiguous field that extended beyond the margins of a clinically visible oral squamous cell carcinoma. Multiple biopsies were taken within this contiguous optically altered field. Genome alterations detected for each specimen were compared to define whether each lesion arose independently or as a consequence of a shared progenitor cell. Our results indicate that the field effect of oral cancer is extremely dynamic, with different genetic alterations present in different biopsies within a field. This case study also demonstrated that 2 genetically unrelated squamous cell carcinoma could be developed within 10 mm at the right lateral tongue of this patient. These findings provide evidence for the importance to implement optical technologies in defining surgical margins and support the use of whole genome technologies in the diagnosis of clonal versus independent lesions of the oral cavity, which may have implications on treatment strategies.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".