Utility of multi focus virtual slide in cytology
Bibliographic record
Abstract
目的: われわれは細胞診に有用なバーチャルスライドの研究を行っている. そして, 顕微鏡操作と同様の 3 次元表示を可能にした「多焦点画像表示装置 パソグラフ」 (以下, パソグラフ) を完成させた. パソグラフは多焦点画像によりフォーカス表示を含み, 光学顕微鏡と変わらぬ操作性と観察を可能にしたバーチャルスライドである. そこで, 単焦点画像と多焦点画像では細胞像の情報量にどのくらいの差が生じるのか検証してみた.方法: 標本は婦人科の細胞診標本を用いた. 比較対象は単焦点, 多焦点それぞれフォーカスを合せられる核の数とし, 単焦点 (s)/多焦点 (m)×100 で比較した.成績: 子宮頸部塗抹標本における対物 20 倍撮影 s/m は平均 20.8%であった. 対物 40 倍撮影の s/m は平均 33.3%であった. 子宮内膜標本における対物 20 倍撮影の s/m は平均 38.7%, 対物 40 倍の s/m は平均 16.8%であった.結論: 単焦点のバーチャルスライドでは細胞標本の情報を十分に表示することはできない. 細胞診のバーチャルスライドには多焦点表示が必須の技術であると思われた.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".