A general method for baseline-removal in ultrafast electron powder diffraction data using the dual-tree complex wavelet transform
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Bibliographic record
Abstract
The general problem of background subtraction in ultrafast electron powder diffraction (UEPD) is presented with a focus on the diffraction patterns obtained from materials of moderately complex structure which contain many overlapping peaks and effectively no scattering vector regions that can be considered exclusively background. We compare the performance of background subtraction algorithms based on discrete and dual-tree complex (DTCWT) wavelet transforms when applied to simulated UEPD data on the M1–R phase transition in VO2 with a time-varying background. We find that the DTCWT approach is capable of extracting intensities that are accurate to better than 2% across the whole range of scattering vector simulated, effectively independent of delay time. A Python package is available.
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Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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