Image Interpretation Session
Bibliographic record
Abstract
The Image Interpretation Session, more informally known as the “Sunday film panel,” has been a yearly event at the Annual Meeting of the Radiological Society of North America since 1939. This year’s session will follow the tradition of bringing together five experts in radiology, each of whom will be shown two unknown cases. These experts represent the subspecialties of interventional radiology and abdominal imaging, musculoskeletal radiology, pediatric radiology, thoracic imaging, and neurologic imaging. The unknown cases have been assembled from generous contributions by radiologists throughout the United States. The selected cases come from Duke University, University of California San Francisco, Mayo Clinic, Massachusetts General Hospital, and University of California San Diego. Many other institutions also proffered cases, which allowed for a wealth of material from which to choose; unfortunately, only 10 cases can be selected. Many thanks to all who contributed material! The cases were generally chosen to provide a challenge to the experts and a learning experience for the audience. The forum of the film panel should not be viewed as a car race, with the spectators waiting for a crash. Instead, it represents an opportunity to observe expert radiologists as they analyze images and develop a differential diagnosis and then use that differential diagnosis to guide patient care. Radiologists must do more than simply describe the findings seen on images. In the current practice environment with highly sophisticated imaging equipment and techniques, we must make sure that we are not so entranced by the images that we forget they are tools for providing better patient care. We must use our experience to suggest appropriate diagnoses; to contribute to patient management; and, in the case of interventional radiologists, to intervene when necessary. The unknown cases will be shown not only at the RSNA annual meeting in McCormick Place, Chicago, but they will also be available online with streaming audio and images on the RSNA Web site. Radiologists from every region of the world can view these images and test their own abilities to analyze images, describe findings, develop a differential diagnosis, and intervene. The ability to communicate electronically allows us to share this experience. We invite the radiologists from around the globe to participate. © RSNA, 2006
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.660 | 0.403 |
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".