Abstract 2004: 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 tumour 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 October 2012, the ICGC has received commitments from researchers and funding organizations in Asia, Australia, Europe and North America for 47 project teams in 15 jurisdictions to study more than 21,000 tumour genomes. Over 23,000 tumours that meet ICGC requirements for consent have been obtained and over 20,000 samples have been approved by research pathologists as meeting ICGC standards. Raw datasets exist for > 10,000 tumours, including > 1,700 whole genome sequences, > 5,130 exomes, > 9,700 copy number alterations, > 4,900 transcriptomes (RNASeq) and over 6,600 methylomes. Processed data is available via the Data Coordination Centre (http://dcc.icgc.org) based at the Ontario Institute for Cancer Research and is updated bimonthly. The latest data release (Version 10) in October 2012 includes datasets from 33 ICGC members and five additional groups. In total, ICGC data release 10 comprises data from 7,022 cancer genomes. In the next five years, ICGC will deliver on its initial and new objectives, including 1) sequencing a cumulative number of >25,000 tumour genomes from 50 or more tumour types, 2) improving data quality of ICGC datasets; 3) developing a scalable software infrastructure to support data management and cancer genome research; 4) streamlining data access mechanisms to accelerate usage and downstream discoveries without compromising the need to protect patient confidentiality; 5) coordinating cross-tumour analyses; 6) and training basic and clinician scientists to use ICGC datasets and tools. More information can be found on www.icgc.org Citation Format: Thomas J. Hudson, Jennifer L. Jennings. International Cancer Genome Consortium (ICGC). [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2004. doi:10.1158/1538-7445.AM2013-2004
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.011 | 0.043 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.175 | 0.123 |
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".