[Invasive infra centimetric breast lobular carcinoma: ultrasonographic features].
Bibliographic record
Abstract
PURPOSE: To evaluate the ability of breast ultrasound to detect and analyze small (less than 1 cm in size) invasive lobular carcinomas. MATERIAL: and methods. A retrospective analysis of 93 small invasive carcinomas measuring less than 10 mm in size diagnosed between 1998 and 2000 in our institution was performed. In this group, 15 invasive lobular carcinomas were identified in 12 patients. All mammograms and ultrasound examinations were reviewed. RESULTS: Twelve cases of less than 10 mm invasive lobular carcinomas were diagnosed. Two lesions in one patient and one in an other patient were not detected at ultrasound and mammogram (multifocal carcinomas). All invasive lobular carcinomas were found as hypoechogenic masses with ill-defined margins and posterior shadowing. Four lesions showed evidence of microlobulations, 6 lesions an hyperechogenic halo and only one showed a vertical axis. The sensitivity of ultrasound in this group was recorded as 80% (12/15). CONCLUSION: The study confirms a high sensitivity of ultrasound examination in detection and characterization of small infiltrative lobular carcinoma.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 0.001 |
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".