Bibliographic record
Abstract
Detecting Her2 gene amplification has become routine in predicting therapeutic responsiveness in patients with breast carcinoma. Fluorescence in situ hybridization (FISH) is a common technique for detecting Her2 amplification, yet dark field fluorescence microscopy remains problematic for many pathologists. Thus, a technique such as chromogenic in situ hybridization (CISH), in which the more familiar light microscopy can be used, is appealing. Paraffin-embedded sections from 61 breast carcinomas were tested for Her2 amplification by immunohistochemistry (IHC) and CISH. FISH was used to confirm CISH results. Excellent correlation was found between IHC and CISH except in cases considered negative (1+ on the DAKO scale) by IHC. CISH detected low-level Her2 amplification in 4 of 9 of these cases. Amplification was subsequently confirmed by FISH in all but 1 case. When compared with FISH, CISH was more sensitive than IHC for detecting low levels of Her2 gene amplification. Moreover, excellent concordance was found between FISH and CISH, supporting the conclusion that the CISH assay for Her2 gene amplification provides an accurate, effective, and practical alternative to FISH.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.012 | 0.004 |
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".