Invasive papillary ductal carcinoma of the breast: A case report
Bibliographic record
Abstract
The general rate of intrusive papillary carcinoma (IPC) is uncommon, representing for less than 1-2 % of invasive breast cancers. They are most generally observed in postmenposal females and uncommon in males. Invasive papillary carcinomas are low grade tumors originating from large or dilated ducts. They are make out of all around outlined solid nodules of monotones neoplastic cell separated by network of fibrovascular cores, IPC is a remarkable sort of breast cancer and regarded of whether it is in-situ or invasive, it has brilliant prognosis. We presenting two cases of invasive papillary carcinoma in male and female; A case of 55years postmenoposal female who presented with history of left breast mass, which this mass notice after trauma same site for 1 year ago the mass gradually increase in size no tenderness, no signs of inflammation. Excisional biopsy was performed and specimen was histopathology diagnosed as invasive papillary carcinoma, left MRM was performed and histopathology diagnosis confirmed and without residual tumor seen in submitted slides and all submitted lymph nodes were free of tumor infiltration (0/14). IHC show ER and PR negative with HER-2 positive. The second case 70 years male presented with right breast mass and history of post-trauma since one year back with gradual increase in size, right radical mastectomy done and histopathology diagnosed as invasive papillary carcinoma, IHC was done ER and PR positive with HER2- negative.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".