New reporting form for breast cytology
Bibliographic record
Abstract
日本乳癌学会規約委員会「細胞診及び生検材料検討小委員会」では, 乳腺細胞診における新たな報告様式を設定した. この報告様式は「判定区分」と「所見」から構成され,「判定区分」は, さらに「検体不適正」,「検体適正」の2つに大別,「検体適正」は “正常あるいは良性”,“鑑別困難”,“悪性の疑い”,“悪性” の4項目に細分されている.「所見」については, 細胞像のほかに推定される組織型を可能な限り記述することを明記した. また, 報告様式設定に当たって解析した細胞診3,439例によって,「検体不適正」は総症例の10%以下,“鑑別困難” は検体適正症例の10%以下, さらに “悪性の疑い” はその後の組織学的検索で悪性と診断された症例が90%以上を占めることを付帯事項 (努力目標) として定めた. 上記報告様式は針生検の報告様式とともに, 乳癌取扱い規約 (第15版) に掲載されるが, 時代の変遷とともに新たな修正, 変更の必要性が生じてくると思われる. その折には本報告様式で行ったようにevidenceの元に改訂していただくことを望んでいる.
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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 | 0.009 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.504 | 0.305 |
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".