NCI Summer Curriculum in Cancer Control and Prevention – A Practice Changing Course for Oncologists from LimitedResource Country Like India
Bibliographic record
Abstract
Cancer has become an important public health issue in India. Oncologists in India spends most of their time in diagnosis and treatment of cancer patients. There is a large disparity geographically as far as cancer treatment facilities are concerned. Cancer control and cancer prevention is not a point of concern for most of the practicing oncologist. Although things are changing in India, but orientation, passion and dedication towards cancer prevention is still missing. There is no program on basic principles and practice of cancer control and prevention in India which addresses the essence of cancer control and prevention. Center for Global Health of National Cancer Institute, USA initiated summer curriculum is an excellent academic program to teach health care professionals working in cancer care in different parts of world. This covers all aspect of cancer care i.e. cancer education, epidemiology, screening, diagnosis, treatment and the before world palliative care with dedicated session on upcoming molecular prevention in cancer. This gives an unique opportunity for learning and can be practice changing curriculum for many of the attendees who want to pursue a career in cancer control and prevention a before practice.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.027 | 0.008 |
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".