Current Activities of the Coalition of Cancer Cooperative Groups
Bibliographic record
Abstract
The Coalition of Cancer Cooperative Groups is an organization representing the interests of patients and researchers who conduct research through the National Cancer Institute-supported National Clinical Trials Network (NCTN). The NCTN provides a crucial mechanism for executing practice-changing cancer clinical research to achieve both cancer control and development of new therapeutic agents or modality approaches. Public funding, largely through the National Cancer Institute, ensures that the work of the NCTN achieves important research that would not otherwise be accomplished in the private sector. In fall 2017, the Coalition of Cancer Cooperative Groups convened a Scientific Leadership Council to review the current state of the network with regard to research capabilities and to develop a list of research questions to be prioritized by the network. This report presents the results of this meeting, detailing a roadmap for future work by the NCTN.
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 | 0.133 | 0.104 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.008 | 0.018 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.019 | 0.005 |
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".