Accurate measurement of relative tilt and azimuth angles in electron tomography: A comparison of fiducial marker method with electron diffraction
Bibliographic record
Abstract
Electron tomography is a method whereby a three-dimensional reconstruction of a nanoscale object is obtained from a series of projected images measured in a transmission electron microscope. We developed an electron-diffraction method to measure the tilt and azimuth angles, with Kikuchi lines used to align a series of diffraction patterns obtained with each image of the tilt series. Since it is based on electron diffraction, the method is not affected by sample drift and is not sensitive to sample thickness, whereas tilt angle measurement and alignment using fiducial-marker methods are affected by both sample drift and thickness. The accuracy of the diffraction method benefits reconstructions with a large number of voxels, where both high spatial resolution and a large field of view are desired. The diffraction method allows both the tilt and azimuth angle to be measured, while fiducial marker methods typically treat the tilt and azimuth angle as an unknown parameter. The diffraction method can be also used to estimate the accuracy of the fiducial marker method, and the sample-stage accuracy. A nano-dot fiducial marker measurement differs from a diffraction measurement by no more than ±1°.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".