Oral Submucous Fibrosis: An Eastern Disease In The Western World
Bibliographic record
Abstract
Oral submucous fibrosis is a chronic, debilitating and pre-malignant disease; it is also one that is not taught in any significant detail in most medical curricula. The clearest association is with the practice of chewing betel quid containing areca nut, a habit very common amongst South Asian populations. With current migration trends and the establishment of large South Asian communities in the Western world, the disease is being seen with increasing frequency where it was previously seldom encountered. With this background in mind, we aim to present a concise overview of the disease and its prognosis so as to create awareness about an issue of emerging public health relevance. Furthermore, since the etiology is mostly linked to a habit, healthcare professionals have a very important role to play in terms of lifestyle modification advice, which may significantly decrease disease incidence, progression and morbidity, if not mortality.
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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 | 0.001 | 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) | 0.003 | 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 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".