Bibliographic record
Abstract
In this study the effects of ASIR™ and collimation on CT image quality (IQ) parameters were quantified. Catphan®600 phantom studies were performed on a GE HD750 64-slice scanner to investigate the impact of collimation 0.625mm vs. 5mm on the overall IQ. For noise and dose reduction ASIR™ was tested on 0.625mm collimation. The varying %ASIR™, scanned at 150mA and variable kVp and 50% ASIR™ compared to FBP on wide kVp/mA range was used. Image noise, CT# accuracy and uniformity, spatial and contrast resolution, MTF, CNR and Wiener spectrum analysis were performed on 0.625mmAX slices, 5mmAXMPR and 2mmCORMPR. Incremental advantages and disadvantages were seen with stepwise increase in %ASIR™. The 50% ASIR™ was found to be optimal blend for diagnostic quality and has potential for dose reduction in paediatric CT. This quantitative data could be used to design ASIR™-enhanced protocols with consideration of diagnostic task, balancing image quality and radiation dose.
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 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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".