The Value of a Monoclonal Anti-Epithelial Antibody (mAB lu-5) in the Differential Diagnosis of Tumors
Bibliographic record
Abstract
The usefulness of a monoclonal anti-epithelial antibody, mAB lu-5, was assessed in the histologic differential diagnosis of 102 formalin-fixed, paraffin-embedded tumors including various carcinomas, sarcomas and lymphomas. A variety of nontumorous tissues were also evaluated. Although mAB lu-5 failed to provide conclusive results in a few cases, in general, it was found to be a reliable immunohistochemical marker of tumorous and nontumorous epithelial cells. Immunostaining with mAB lu-5 did not distinguish between tumorous and nontumorous tissues and between benign and malignant tumors. Further work is required to clarify the significance of strong immunoreactivity noted in chorionic epithelium and pituitary corticotrophs.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".