On-call services provided by radiology residents in a university hospital environment.
Bibliographic record
Abstract
OBJECTIVE: To better understand the consultative role of the radiology resident after hours. METHODS: Data were collected prospectively from Mar. 15, 1999, to Jan. 5, 2001, during on-call coverage hours at our university hospital. Urgent radiologic examinations for which the on-call resident rendered a preliminary interpretation were included in our analysis, with the following entered into a database: patient demographics, consultative time and weekday, imaging modality, consulting clinical service and indication for each study. RESULTS: A total of 1784 studies were performed on 1451 patients; most were requested by the emergency department (844 cases [47.3%]). The mean number of radiographic studies performed was 20.1 (standard error of the mean [SEM] 1.1) per weekday (n = 44) and 49.4 (SEM 1.8) per weekend day or holiday (n = 18). There were 1227 (68.8%) computed tomographic (CT), 338 (18.9%) ultrasonographic, 98 (5.5%) plain radiograph, 63 (3.5%) nuclear medicine, 21 (1.2%) interventional, 20 (1.1%) fluoroscopic and 17 (1.0%) magnetic resonance imaging examinations. The 3 most common studies were CT of the head in 692 cases, CT of the abdomen in 230 and venous Doppler ultrasonography in 158. CONCLUSIONS: Radiology residents are performing a diverse and increasing number of emergent diagnostic examinations after hours. It is therefore important that radiology departments are aware of these consultative needs to best ensure that appropriate resident skills are developed to meet these demands.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".