Awareness and knowledge of oral cancer in the city of Baghdad, Iraq: a questionnaire-based survey
Bibliographic record
Abstract
ENWEndNote BIBJabRef, Mendeley RISPapers, Reference Manager, RefWorks, Zotero AMA Alshami ML, Abdulbaqi HR, Abdulkareem AA. Awareness and knowledge of oral cancer in the city of Baghdad, Iraq: a questionnaire-based survey. Journal of Stomatology. 2019;72(6):263-268. doi:10.5114/jos.2019.93796. APA Alshami, M. L., Abdulbaqi, H. R., & Abdulkareem, A. A. (2019). Awareness and knowledge of oral cancer in the city of Baghdad, Iraq: a questionnaire-based survey. Journal of Stomatology, 72(6), 263-268. https://doi.org/10.5114/jos.2019.93796 Chicago Alshami, Muhanad L, Hayder R Abdulbaqi, and Ali A Abdulkareem. 2019. "Awareness and knowledge of oral cancer in the city of Baghdad, Iraq: a questionnaire-based survey". Journal of Stomatology 72 (6): 263-268. doi:10.5114/jos.2019.93796. Harvard Alshami, M., Abdulbaqi, H., and Abdulkareem, A. (2019). Awareness and knowledge of oral cancer in the city of Baghdad, Iraq: a questionnaire-based survey. Journal of Stomatology, 72(6), pp.263-268. https://doi.org/10.5114/jos.2019.93796 MLA Alshami, Muhanad et al. "Awareness and knowledge of oral cancer in the city of Baghdad, Iraq: a questionnaire-based survey." Journal of Stomatology, vol. 72, no. 6, 2019, pp. 263-268. doi:10.5114/jos.2019.93796. Vancouver Alshami M, Abdulbaqi H, Abdulkareem A. Awareness and knowledge of oral cancer in the city of Baghdad, Iraq: a questionnaire-based survey. Journal of Stomatology. 2019;72(6):263-268. doi:10.5114/jos.2019.93796.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".