Sci‐PM Sat ‐ 01: Imaging performance of a bench‐top megavoltage CT scanner
Bibliographic record
Abstract
The ultimate goal of this project is to create a focused 2D MV detector with high detective quantum efficiency so reasonable low contrast resolution (LCR) at low dose can be obtained in MVCT. As an initial step an 80‐element detector is fabricated by tiling 8‐element (element size 0.275 × 0.8 × 1 cm 3 ) and photodiode arrays on an arc (radius = 110 cm). A precision rotary stage and its control are added to create a third generation CT scanner. The attenuation of and 6 MV beams are measured as a function of solid water thickness, fit to a second order polynomial to correct for spectral hardening artifacts. A calibration procedure was established to remove ring artifacts caused by distinctly asymmetric line spread functions at the ends of 8‐element blocks. Low contrast resolution as a function of dose and object size, the signal to noise ratio (SNR) as a function of dose, and linearity of CT numbers with density were quantified. Throwing away one‐ninth of collected projection angles to reduce the dose per image adversely affects the resolution in 6 MV images; 15 mm targets at 1.5% are visible at 7cGy. Low contrast target of 1.5% at 6 mm is visible in at 2cGy. LCR in objects stays approximately constant while dose is reduced from 17 to 2cGy. Contrast decreases with diameter decrease. SNR 2 from a uniform phantom increases linearly with dose (R 2 =0.9977). CT numbers as a function of the density show a linear trend (R 2 =0.9923).
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 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) | 0.000 | 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".