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Record W2117678619 · doi:10.1139/o08-003

From cytogenetics to next-generation sequencing technologies: advances in the detection of genome rearrangements in tumorsThis paper is one of a selection of papers published in this Special Issue, entitled CSBMCB — Systems and Chemical Biology, and has undergone the Journal's usual peer review process.

2008· review· en· W2117678619 on OpenAlexaffvenue
Olena Morozova, Marco A. Marra

Bibliographic record

VenueBiochemistry and Cell Biology · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomic variations and chromosomal abnormalities
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsGenomeBiologyComputational biologyDNA sequencingHuman genomeCancer genome sequencingSelection (genetic algorithm)Personal genomicsScope (computer science)GeneticsComputer scienceGeneArtificial intelligence

Abstract

fetched live from OpenAlex

Genome rearrangements have long been recognized as hallmarks of human tumors and have been used to diagnose cancer. Techniques used to detect genome rearrangements have evolved from microscopic examinations of chromosomes to the more recent microarray-based approaches. The availability of next-generation sequencing technologies may provide a means for scrutinizing entire cancer genomes and transcriptomes at unparalleled resolution. Here we review the methods that have been used to detect genome rearrangements and discuss the scope and limitations of each approach. We end with a discussion of the potential that next-generation sequencing technologies may offer to the field.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.394
Threshold uncertainty score0.568

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.037
GPT teacher head0.273
Teacher spread0.236 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreReview

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".

Quick stats

Citations55
Published2008
Admission routes2
Has abstractyes

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