Bibliographic record
Abstract
Coherent scatter x-ray imaging systems are sensitive to material structure and chemical composition, and generate images with contrast superior to conventional transmission xray imaging.The goal of this thesis was to develop a scatter projection imaging system capable of acquiring images in less than ten minutes, in the range of nuclear medicine scans, to be practical for future applications such as bone specimen imaging.Two systems were developed.The first improved on the group's previous work and was configured at the Canadian Light Source synchrotron.It employed five 33.2 keV pencil beams in combination with continuous object motion.The system consisted of a primary collimator, motorized stages for object translation, a flat-panel x-ray detector for measuring scattered x rays, and discrete photodiodes for simultaneously measuring transmitted x rays.The acquisition time for a 5.0 cm × 9.0 cm object with 8425 pixels was 2.3 min.Use of continuous motion acquisition increases the width of image boundaries by the product of the object translation speed and the acquisition time per pixel.Contrast-detail performance was independent of acquisition speed.Pixel signal-to-noise ratio (SNR) measurements indicated that the scatter data were limited by the detector readout noise.The synchrotron system was a development stage in an idealized environment but a practical system requires a commonly available x-ray source.Therefore, a second system was developed using a conventional rotating-anode x-ray tube.An array of up to three rows by five columns of pencil beams can irradiate the object simultaneously.A 110 kVp spectrum with 2.25 mm of added Al filtration was used.Motorized stages translate the object through the beams for step-and-shoot acquisition.For this first x-ray tube-based system, the primary imaging capability was not optimized and transmitted x rays are mea-My sincerest thanks go to my supervisor Paul Johns who provided help, suggestions, and support throughout my graduate studies.At the BMIT facility at the Canadian Light Source (CLS), special thanks go to George Belev, now at the Saskatchewan Structural Sciences Centre, who worked with us late into the night to ensure we had a working system to complete our experiments in the allocated beam time.Thanks also to BMIT staff
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".