Canadian Society of Thoracic Radiology/Canadian Association of Radiologists Best Practice Guidance for Investigation of Acute Pulmonary Embolism, Part 1: Acquisition and Safety Considerations
Bibliographic record
Abstract
Acute pulmonary embolism (APE) is a well-recognized cause of circulatory system compromise and even demise which can frequently present a diagnostic challenge for the physician. The diagnostic challenge is primarily due to the frequency of indeterminate presentations as well as several other conditions which can have a similar clinical presentation. This often obliges the physician to establish a firm diagnosis due to the potentially serious outcomes related to this disease. Computed tomography pulmonary angiography (CTPA) has increasingly cemented its role as the primary investigation tool in this clinical context and is widely accepted as the standard of care due to several desired attributes which include great accuracy, accessibility, rapid turn-around time and the ability to suggest an alternate diagnosis when APE is not the culprit. In Part 1 of this guidance document, a series of up-to-date recommendations are provided to the reader pertaining to CTPA protocol optimization (including scan range, radiation and intravenous contrast dose), safety measures including the departure from breast and gonadal shielding, population-specific scenarios (pregnancy and early post-partum) and consideration of alternate diagnostic techniques when clinically deemed appropriate.
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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 | 0.004 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.057 | 0.032 |
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".