WE HAVE MORE EVIDENCE THAN BEFORE; ULTRASONOGRAPHY IS A RELIABLE TOOL TO SHOW RIB FRACTURES
Bibliographic record
Abstract
OBJECTIVE: The aim of this study is to assess the value of ultrasonography (US) by determining the inter-observer reliability on US evaluation of suspected rib fractures in blunt chest trauma. MATERIAL AND METHODS: A total of 52 patients (32 males, 20 females) with a mean age of 48 years (18-95 years) who presented to the emergency department with blunt chest trauma and suspected rib fracture were included in the study. All patients were assessed with US by two radiologists (a senior radiologist with 20 years of US experience and a resident with one year of US experience) independently and chest x-rays were also evaluated. RESULTS: Only two rib fractures were detected on chest x-rays. 22 fractures were detected from 19 patients with US by both radiologists. One rib fracture was noted only by the senior radiologist and not by the resident. Interobserver agreement was very good (kappa: 0.917) and statistically significant (p=0.002). All fractures were located at the bony portion of the rib and no fracture was found at the costal cartilage or costochondral junction. CONCLUSIONS: We demonstrated that US is a highly reproducible diagnostic tool for rib fractures with very low inter-observer variability.
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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 | 0.014 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".