An Integrated X-Ray/Optical Tomography System for Pre-clinical Radiation Research
Bibliographic record
Abstract
The current Small Animal Radiation Research Platform (SARRP) is poor for localizing small soft tissue targets for irradiation or tumor models growing in a soft tissue environment. Therefore, an imaging method complementary to x-ray CT is required to localize the soft tissue target’s Center of Mass (CoM) to within 1 mm. In this paper, we report the development of an integrated x-ray/bioluminescence imaging/tomography (BLI/BLT) system to provide a pre-clinical, high resolution irradiation system. This system can be used to study radiation effects in small animals under the conebeam computed tomography (CBCT) imaging guidance by adding the bioluminescence imaging (BLI) system as a standalone system which can also be docked onto the SARRP. The proposed system integrates two robotic rotating stages and an x-ray source rated at maximum 130 kVp and having a small variable focal spot. A high performance and low noise CCD camera mounted in a light-tight housing along with an optical filter assembly is used for multi-wavelength BL tomography. A three-mirror arrangement is implemented to eliminate the need of rotating the CCD camera for acquiring multiple views. The mirror system is attached to a motorized stage to capture images in angles between 0–90° (for the standalone system). Camera and CBCT calibration are accomplished.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.012 | 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".