FISH Detection of HER2 Amplification in Breast Cancer
Bibliographic record
Abstract
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.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".