A Novel Analyzer Control System for Diffraction Enhanced Imaging
Bibliographic record
Abstract
Diffraction Enhanced Imaging is an imaging modality that derives contrast from x-ray refraction, an extreme form of scatter rejection (extinction) and absorption which is common to conventional radiography. A critical part of the imaging system is the "analyzer crystal" which is used to re-diffract the beam after passing through the object being imaged. The analyzer and monochromator crystals form a matched parallel crystal set. This analyzer needs to be accurately aligned and that alignment maintained over the course of an imaging session. Typically, the analyzer needs to remain at a specific angle within a few tens of nanoradians to prevent problems with image interpretation. Ideally, the analyzer would be set to a specific angle and would remain at that angle over the course of an imaging session which might be from a fraction of a second to several minutes or longer. In many instances, this requirement is well beyond what is possible by relying on mechanical stability alone and some form of feedback to control the analyzer setting is required. We describe a novel analyzer control system that allows the analyzer to be set at any location in the analyzer rocking curve, including the peak location. The method described is extensible to include methods to extend the range of analyzer control to several Darwin widths away from the analyzer peaked location. Such a system is necessary for the accurate implementation of the method and is intended to make the use of the method simpler without relying on repeated alignment during the imaging session.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".