Signal to noise considerations for single crystal femtosecond time resolved crystallography of the Photoactive Yellow Protein
Bibliographic record
Abstract
Femtosecond time resolved pump-probe protein X-ray crystallography requires highly accurate measurements of the photoinduced structure factor amplitude differences. In the case of femtosecond photolysis of single P63 crystals of the Photoactive Yellow Protein, it is shown that photochemical dynamics place a considerable restraint on the achievable time resolution due to the requirement to stretch and add second order dispersion in order to generate threshold concentration levels in the interaction region. Here, we report on using a 'quasi-cw' approach to use the rotation method with monochromatic radiation and 2 eV bandwidth at 9.465 keV at the Linac Coherent Light Source operated in SASE mode. A source of significant Bragg reflection intensity noise is identified from the combination of mode structure and jitter with very small mosaic spread of the crystals and very low convergence of the XFEL source. The accuracy with which the three dimensional reflection is approximated by the 'quasi-cw' rotation method with the pulsed source is modelled from the experimentally collected X-ray pulse intensities together with the measured rocking curves. This model is extended to predict merging statistics for recently demonstrated self seeded mode generated pulse train with improved stability, in addition to extrapolating to single crystal experiments with increased mosaic spread. The results show that the noise level can be adequately modelled in this manner, indicating that the large intensity fluctuations dominate the merged signal-to-noise (I/σI) value. Furthermore, these results predict that using the self seeded mode together with more mosaic crystals, sufficient accuracy may be obtained in order to resolve typical photoinduced structure factor amplitude differences, as taken from representative synchrotron results.
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How this classification was reachedexpand
Full frame distilled prediction
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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".