Canadian Society of Thoracic Radiology/Canadian Association of Radiologists Best Practice Guidance for Investigation of Acute Pulmonary Embolism, Part 2: Technical Issues and Interpretation Pitfalls
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
The investigation of acute pulmonary embolism is a common task for radiologists in Canada. Technical image quality and reporting quality must be excellent; pulmonary embolism is a life-threatening disease that should not be missed but overdiagnosis and unnecessary treatment should be avoided. The most frequently performed imaging investigation, computed tomography pulmonary angiogram (CTPA), can be limited by poor pulmonary arterial opacification, technical artifacts and interpretative errors. Image quality can be affected by patient factors (such as body habitus, motion artifact and cardiac output), intravenous (IV) contrast protocols (including the timing, rate and volume of IV contrast administration) and common physics artifacts (including beam hardening). Mimics of acute pulmonary embolism can be seen in normal anatomic structures, disease in non-vascular structures and pulmonary artery filling defects not related to acute pulmonary emboli. Understanding these pitfalls can help mitigate error, improve diagnostic quality and optimize patient outcomes. Dual energy computed tomography holds promise to improve imaging diagnosis, particularly in clinical scenarios where routine CTPA may be problematic, including patients with impaired renal function and patients with altered cardiac anatomy.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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