A Systematic Review On The Prevalence Of Oral Cancer Among Tobacco And Non-Tobacco Users In Tamil Nadu
Bibliographic record
Abstract
Background: Oral Cancer Is One Of The World's Most Common Types Of Cancer, With Delayed Diagnosis And Poor Prognosis. IndiaIs Among The Leading Countries With A High Rate Of Oral Cancer Due To Its Increased Tobacco Use Rate.Aim: This Study Aims To Assess The Prevalence Of Oral Cancer Among Tobacco And Non-Tobacco Users In Tamil Nadu.Materials And Method: A Systematic Review Of Cross-Sectional Studies Were Performed. The Data Was Searched Using ElectronicDatabases, And 376 Articles Were Screened. The Intervention And Outcomes Were Assessed In The Studies Included In TheSystematic Review. The Bias Assessment Done For The Article Was Based On The Newcastle-Ottawa Scale.Results: Overall Analysis Of The Studies Shows That The Prevalence Of Oral Cancer In Tamil Nadu Has Been Significantly IncreasingAnd That Smokeless Tobacco Causes Oral Cancer Compared With Other Forms Of Tobacco.Conclusion: The Prevalence Of Oral Cancer In Tamil Nadu Is Increasing Significantly With The Usage Of The Increased Amount OfTobacco, And Awareness Of The Ill Effects Of Tobacco Usage May Considerably Decrease The Rates.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".