Optimization of Computed Tomography Coronary Angiography for Improved Plaque Detection
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: The study aims to optimize visualization of the coronary wall during computed tomography coronary angiography. METHODS: A coronary plaque phantom was scanned on a wide-volume computed tomography scanner. Spatial resolution, contrast resolution, and vessel wall thickness were measured at different x-ray tube currents and voltages. RESULTS: Spatial resolution ranged from 0.385 to 0.625 mm and was significantly lower at higher currents. Contrast-to-noise ratio was significantly higher at higher currents. The most accurate wall thickness measurements were quantified at 300 and 400 mA for 80 and 100 kVp and 300 mA for 120 and 135 kVp. CONCLUSIONS: Lower spatial resolution at higher currents was due to added blur from increased focal spot size. Contrast-to-noise ratio was higher at higher currents owing to decreased quantum noise. Wall thickness was measured more accurately at intermediate currents with midrange contrast-to-noise ratio but optimal spatial resolution. For accurate coronary wall thickness measurement, contrast-to-noise ratio is compromised to achieve optimal spatial resolution.
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.
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) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 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 it