CASINO V2.42—A Fast and Easy‐to‐use Modeling Tool for Scanning Electron Microscopy and Microanalysis Users
Bibliographic record
Abstract
Monte Carlo simulations have been widely used by microscopists for the last few decades. In the beginning it was a tedious and slow process, requiring a high level of computer skills from users and long computational times. Recent progress in the microelectronics industry now provides researchers with affordable desktop computers with clock rates greater than 3 GHz. With this type of computing power routinely available, Monte Carlo simulation is no longer an exclusive or long (overnight) process. The aim of this paper is to present a new user-friendly simulation program based on the earlier CASINO Monte Carlo program. The intent of this software is to assist scanning electron microscope users in interpretation of imaging and microanalysis and also with more advanced procedures including electron-beam lithography. This version uses a new architecture that provides results twice as quickly. This program is freely available to the scientific community and can be downloaded from the website: (www.gel.usherb.ca/casino).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.044 | 0.007 |
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".