Po‐Poster ‐ 32: Optimization of an x‐ray diffraction experiment via numerical calculations
Bibliographic record
Abstract
In our lab, a research program focused on identifying breast cancer by measuring the x‐ray scatter signals is under development. In an attempt to help us determine how the misalignment of the experimental setup and the fluorescence escaping affect our measured results in our particular experimental conditions, we have developed a set of simulation programs written in C++ object‐oriented language. We use a 5 mm diameter 5 mm thick water target as our sample and a cadmium zinc telluride detector. We have simulated the scattering in the sample, incorporated misalignments in our system and studied the effects of K‐fluorescence escape from our detector. We simulate monoenergetic beams with energies of 15 keV, 25 keV, and 35 keV. We also consider a 50 kV x‐ray spectrum. The angles studied range from 5° to 16° . The misalignments are that the beams on either the target or the detector are offset by (0.5mm, 0.5mm) or (−0.5mm, −0.5mm) from the center, or the detector angle has an offset of ±0.2 degrees. We find small percent differences ranging from −1.65% to 4.91% for aligned versus misaligned geometries. We anticipate that we can align our system to obtain good results. The K‐fluorescence escape probability varies as a function of the incoming photon energy and the depth of interaction in the detector. The highest escape probability of 11% occurs for a photon energy of about 33 keV. The escaping is essentially from the top surface of our detector and we may need to take this effect into account.
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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) | 0.002 | 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".