Abstract 5063: International Cancer Genome Consortium (ICGC)
Bibliographic record
Abstract
Abstract The International Cancer Genome Consortium (ICGC) was established to bring together researchers from around the globe to comprehensively analyze the genomic, transcriptomic, and epigenomic changes in 50 different tumor types or subtypes that are of clinical and societal importance across the globe. (International network of cancer genome projects (Nature 464, 993-998 (15 April 2010)). As of November 2011, the ICGC has received commitments from funding organizations in Asia, Australia, Europe and North America for 43 project teams in 13 jurisdictions to study over 18,000 tumor genomes. The genomic analyses of tumors conducted by ICGC members in Australia and Canada (pancreatic cancer), Japan (liver cancer), Spain (blood cancer), the UK (breast, lung and skin cancer) and the USA (blood, brain, breast, colon, kidney, lung, ovarian, rectal, stomach and uterine cancer) are now available through the Data Coordination Center housed on the ICGC website at www.icgc.org. The ICGC's informed consent and ethical oversight policies state that cancer patients enrolled in an ICGC-related study should be informed that their participation is voluntary, that their clinical care will not be affected by their participation and that data obtained from analyses using their samples will be made available to the international research community. Ultimately, over 25,000 tumor genomes will be sequenced worldwide. This will provide a comprehensive catalogue of genomic abnormalities associated with cancer, a collection of data that will reveal the repertoire of mutations that cause this wide-ranging disease and help define clinically relevant subtypes of cancer. The data will also provide a rich resource for the world's researchers who are working to develop new treatments to make patient care move forward. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 5063. doi:1538-7445.AM2012-5063
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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 | 0.027 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.015 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.075 | 0.028 |
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".