Bibliographic record
Abstract
Oral cancers are by definition, cancers of the lip, tongue and mouth. Combined together with pharyngeal cancers, oral cancer is the 6th most common cancer in the world. Although the incidence of oral cancer is greater in certain parts of the world, such as South and South East Asia, certain parts of France, Eastern Europe, Latin America, Caribbean and the Pacific Region, it is prevalent all over the world Oral Cancer has an annual global incidence of about 275,000. The 5 year survival rates for oral cancer remained at about 50% during the greater part of the twentieth century. However, a recent improvement in the oral cancer survival rates has been observed with the 2010 reported rates being as high as 65.5%. The 5 year survival rates vary according to the site and the stage at which detected.An improvement in the survival rate has been seen in the past few years in certain parts of the world, such as Canada, owing to a reduction in related risk factors, such as smoking. Poor survival rate among the oral cancer patients has been attributable to the advanced extent of the disease at the time of diagnosis. More than 60% of these cancers are diagnosed when the patient has already reached 4 stages III or IV of the cancer.Oral cancer arises in the surface oral epithelium, which is easily accessible for direct visual and tactile examination. It is known, through evidence that survival rates of oral cancer vary according to the stage of cancer at the time of diagnosis. A randomised controlled trial study reported that 5 year survival rates for oral cancer diagnosed at stage I is 66.2%, while that for a cancer diagnosed at stage IV is 22.2%. Early diagnosis of oral cancer increases the survival rate, improving the quality of life along with that. Also, the cost of treating an oral cancer patient at stage IV is three times that of treating one at stage I.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".