Assessment of Deformation using the Focused Ion Beam Technique
Bibliographic record
Abstract
Abstract Focused Ion Beam (FIB) micromachining techniques have gained significant attention over the past few years as a promising method for the preparation of a variety of metallic and nonmetallic materials for subsequent characterization using transmission electron microscopy (TEM) The advantage of the FIB in terms of site specificity and speed for the preparation of uniform electron transparent sections has opened a wide range of potential applications in materials characterization. The ability to image the sample in the FIB can also provide important microstructural data for materials analysis. In this study, both conventionally electropolished and FIB-ed specimens were prepared in order to characterize the microstructure of a commercially-produced tube of Alloy 600 (approximately Ni-15 Cr-10 Fe- 0.05 C). The electropolished samples were prepared using a solution of 20% HClO4 - 80% CH3OH at ∼-40°C. The FIB sections were obtained from a cross-section of the tube that had been mechanically thinned to ∼100 μm. The section was thinned in a Micrion 2500 FIB system with a Ga ion beam at 50 kV accelerating voltage.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".