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Record W2417974725 · doi:10.1385/1-59259-300-3:353

FISH Detection of HER2 Amplification in Breast Cancer

2003· article· en· W2417974725 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

VenueMolecular Cytogenetics · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomic variations and chromosomal abnormalities
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsCarcinogenesisBiologyGene duplicationGeneGenome instabilityGenomeChromosomeDNAGeneticsgenomic DNAGene rearrangementMolecular biologyDNA damage

Abstract

fetched live from OpenAlex

Gene amplification is frequently detected in human tumor cells and is thought to make an important contribution to tumorigenesis ( 1 , 2 ). Systematic scanning of the whole genome of tumor cells using comparative genomic hybridization has revealed that gene copy number changes occur concurrently in many areas of the genome in solid tumors ( 3 ). Detailed analysis of altered regions of DNA has revealed complex DNA rearrangements often involving multiple genes and spanning several megabases in solid tumors. Overlaid on gene rearrangements are frequent changes in chromosome ploidy ( 4 – 6 ). The analysis of amplified regions of DNA can lead to the identification of novel genes that contribute to tumorigenesis, but is complicated by the co-amplification of neighboring genes in these large, complex rearrangements. Many tumors show such a high degree of general DNA and chromosome rearrangement that some researchers argue the critical event in tumorigenesis is genomic instability ( 7 – 10 ) with gene amplification being a consequence.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.448

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.007
GPT teacher head0.224
Teacher spread0.216 · 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