<i>LaueGUI</i>– an open source Matlab tool for online inspection of time-resolved Laue diffraction patterns
Bibliographic record
Abstract
Pink beam Laue diffraction is a powerful tool for determining timeresolved crystallographic structure.The large bandwidth compared to a monochromatic beam allows the simultaneous collection of hundreds of reflections even for moderate size unit cells at fixed orientation.Below 100 X-ray pulses are needed due to the high brightness of the pink beam at a synchrotron.This allows fast data collection and limits sample degradation due to laser excitation.However, there is a large gap between the speed of data collection and the speed of analysis tools.The purpose of LaueGUI is to fill this void by rapidly evaluating time-resolved Laue patterns.The program is based on the use of Precognition (Renz Research), but special care has been taken that the software is self contained in the Matlab environment.LaueGUI is open source written in an object oriented style.It's controlled through a graphical user interface (GUI) and loads free format ASCII files for many configurations.The code was executed with MAR165 and MAR133 (MAR Research) images but other detector image formats can be supported.Successful analysis was completed in a few seconds per image with data from ESRF[1], KEK-AR[2] and APS(BioCARS) [3].At ESRF data from TTF-CA single crystals were collected using 50 single pulses of the 16 bunch mode at ID09b (U17, 9mm gap, 18keV, 3% bandwidth) that allowed full structure refinement.Comparable data were collected for organometallic samples at KEK-AR using 3-10 single bunches.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.196 | 0.088 |
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".