International Cancer Genome Consortium Data Portal--a one-stop shop for cancer genomics data
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
The International Cancer Genome Consortium (ICGC) is a collaborative effort to characterize genomic abnormalities in 50 different cancer types. To make this data available, the ICGC has created the ICGC Data Portal. Powered by the BioMart software, the Data Portal allows each ICGC member institution to manage and maintain its own databases locally, while seamlessly presenting all the data in a single access point for users. The Data Portal currently contains data from 24 cancer projects, including ICGC, The Cancer Genome Atlas (TCGA), Johns Hopkins University, and the Tumor Sequencing Project. It consists of 3478 genomes and 13 cancer types and subtypes. Available open access data types include simple somatic mutations, copy number alterations, structural rearrangements, gene expression, microRNAs, DNA methylation and exon junctions. Additionally, simple germline variations are available as controlled access data. The Data Portal uses a web-based graphical user interface (GUI) to offer researchers multiple ways to quickly and easily search and analyze the available data. The web interface can assist in constructing complicated queries across multiple data sets. Several application programming interfaces are also available for programmatic access. Here we describe the organization, functionality, and capabilities of the ICGC Data Portal.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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