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Unraveling the Genetics of Cancer: Genome Sequencing and Beyond

2011· review· en· W2107782176 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnual Review of Genomics and Human Genetics · 2011
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsUniversity of TorontoOntario Institute for Cancer Research
Fundersnot available
KeywordsEpigenomeGenomeBiologyCancer genome sequencingComputational biologyDNA sequencingGeneticsGenomicsWhole genome sequencingCarcinogenesisCancerDNA methylationGene

Abstract

fetched live from OpenAlex

Advances in next-generation sequencing technology are enabling the systematic analyses of whole cancer genomes, providing insights into the landscape of somatic mutations and the great genetic heterogeneity that defines the unique signature of an individual tumor. Moreover, integrated studies of the genome, epigenome, and transcriptome reveal mechanisms of tumorigenesis at multiple levels. Progress in sequencing technologies and bioinformatics will improve the costs, sensitivity, and accuracy of detecting somatic mutations, while large-scale projects are underway to coordinate cancer genome sequencing at the global level to facilitate the generation and dissemination of high-quality uniform genetic data. These developments will create opportunities for deeper studies of cancer genetics and the clinical application of genome sequencing, and will motivate further research in cancer pathogenesis.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.317
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it