Sci-Thurs PM: Planning-10: Commissioning a Four-Dimensional Computed Tomography System for Clinical Implementation
Bibliographic record
Abstract
We recently acquired four-dimensional computed tomography (4DCT) capabilities at our centre with the installation of the Varian Real-time Position Management (RPM) System (Varian Medical Systems, Palo Alto, CA) and pulmonary gating software for our Philips Brilliance Big Bore scanner (Philips Healthcare, Andover, MA). A CIRS Dynamic Thorax Phantom (Model 008) was also purchased for commissioning and quality assurance purposes (Computerized Imaging Reference Systems, Inc., Norfolk, VA). This work describes the results of the tests used to commission the 4DCT system for clinical implementation. Aspects of the 4DCT system tested to date are volume reconstruction accuracy, CT number accuracy, positional accuracy, and the computed tomography dose index (CTDI) for the 4DCT protocol used in this work. Volume and CT number reconstruction accuracy of the system is comparable to previously reported values, and our positional accuracy is on the order of a millimeter. Measurements of the for the protocol used in this work indicate that the average absorbed dose over a given scan volume is an order of magnitude higher than a standard CT scan. We consider the performance of the 4DCT system to be acceptable and are therefore ready to implement it clinically.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.054 | 0.018 |
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".