Comprehensive cancer control-research & development: knowing what we do and doing what we know
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Comprehensive cancer control is defined as an integrated and coordinated approach to reducing cancer incidence, morbidity, and mortality across the cancer control continuum from primary prevention to end-of-life care. This approach assumes that when the public sector, non-governmental organizations, academia, and the private sector share with each other their skills, knowledge, and resources, a country can take advantage of all its talents and resources to more quickly reduce the burden of cancer for all its population. One critical issue for comprehensive cancer control is the extent to which the private sector can contribute to cancer prevention and control programs and policies that have historically been lead by the public health sector, and similarly how can the public sector increase its investment and involvement in clinical research and practice issues that are largely driven by the private sector worldwide? In addition, building capacity to integrate research that is appropriate to the culture and context of the population will be important in different settings, in particular research related to cancer control interventions that have the capacity to influence outcomes. To whatever extent cancer control research is ultimately funded through the private and public sectors, if investments in research discoveries are ultimately to benefit the populations that bear the greatest burden of disease, then new approaches to integrating the lessons learned from science with the lessons learned from service (public health, clinical, and public policy) must be found to close the gap between what we know and what we do. Communities of practice for international cancer control, like the ones fostered by the first three International Cancer Control Congresses, represent an important forum for knowledge exchange opportunities to accelerate the translation of new knowledge into action to reduce the burden of cancer worldwide.
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.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it