Demonstration of Her-2 Protein in Cervical Carcinomas
Bibliographic record
Abstract
OBJECTIVE.: Recently, an immunohistochemical test for her-2-neu has been approved by the Food and Drug Administration for evaluation of breast cancer patients who might benefit from treatment with Herceptin (HercepTest). This study was undertaken to evaluate the immunohistochemical staining patterns in cervical cancer and correlate with clinical parameters. MATERIALS AND METHODS.: A total of 24 cases of invasive squamous cell carcinoma of the cervix were evaluated. Cases were stained using the HercepTest kit according to protocol. Results were graded from 0 to 3+, using the standards set for breast lesions. RESULTS.: A total of 17 cases (70.8%) were negative, 3 cases (12.5%) showed 1+ staining, and 4 cases (16.7%) showed 2+ staining. No cases showed 3+ staining. Higher her-2 staining grade correlated strongly with vaginal margin status. A weak positive correlation was seen between her-2 staining and tumor stage. There was no correlation with tumor grade or histological lymph node status. CONCLUSIONS.: A subset of invasive squamous cell carcinomas of the cervix overexpress her-2 protein. Further studies are needed to correlate with clinical outcome and determine if overexpression of her-2 protein is a marker of cervical carcinoma aggressiveness.
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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) | 0.002 | 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 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".