Survey of terminology used for the intraoperative direction of C-arm fluoroscopy
Bibliographic record
Abstract
BACKGROUND: Orthopedic surgeons depend on the intraoperative use of fluoroscopy to facilitate procedures across all subspecialties. The versatility of the C-arm fluoroscope allows acquisition of nearly any radiographic view. This versatility, however, creates the opportunity for difficulty in communication between surgeon and radiation technologist. Poor communication leads to delays, frustration and increased exposure to ionizing radiation. There is currently no standard terminology employed by surgeons and technologists with regards to direction of the fluoroscope. METHODS: The investigation consisted of a web-based survey in 2 parts. Part 1 was administered to the membership of the Canadian Orthopedic Association, part 2 to the membership of the Canadian Association of Medical Radiation Technologists. The survey consisted of open-ended or multiple-choice questions examining experience with the C-arm fluoroscope and the terminology preferred by both orthopedic surgeons and radiation technologists. RESULTS: The survey revealed tremendous inconsistency in language used by orthopedic surgeons and radiation technologists. It also revealed that many radiation technologists were inexperienced in operating the fluoroscope. CONCLUSION: Adoption of a common language has been demonstrated to increase efficiency in performing defined tasks with the fluoroscope. We offer a potential system to facilitate communication based on current terminology used among Canadian orthopedic surgeons and radiation technologists.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| 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) | 0.002 | 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".