Emerging Technologies for Assessing HER2 Amplification
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.
Bibliographic record
Abstract
Patients with human epidermal growth factor receptor-2 (HER2)+ breast cancer are eligible for trastuzumab treatment; therefore, accurate assessment of HER2 status is essential. Until recently, only 2 methods were validated for determining the HER2 status of breast tumors in the routine diagnostic setting: immunohistochemical analysis and fluorescence in situ hybridization (FISH). Recently, bright-field in situ hybridization techniques such as chromogenic in situ hybridization (CISH) and silver-enhanced in situ hybridization (SISH), which combine features of immunohistochemical analysis and FISH, have been introduced for the determination of HER2 status. These new techniques use a peroxidase enzyme-labeled probe with chromogenic detection, instead of a fluorescent-labeled probe, allowing results to be visualized by standard bright-field microscopy. Thus, the histologic features and HER2 status of a specimen can be evaluated in parallel. Moreover, signals do not decay over time. This review discusses recent publications regarding CISH and SISH testing, including results scoring and concordance between FISH and immunohistochemical analysis.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it