Bibliographic record
Abstract
More than 85% of blunt and penetrating trauma to the thorax results in injury to the lungs or ribs. Among civilians, blunt trauma is the most common mechanism, while penetrating trauma is the most common among military sectors. This review describes the assessment and stabilization, diagnosis, treatment and disposition, and outcomes of thoracic trauma. Videos shows the “lung point” sign on M-mode and two-dimensional ultrasonography, and a transthoracic echocardiogram clip of pericardial clot and tamponade due to a gunshot wound. Figures show a sonogram showing the “lung point sign”, a chest x-ray and computed tomographic scan demonstrating right-sided hemothorax in a patient with a right chest stab wound, and a three-dimensional computed tomographic scan and chest x-ray of a blunt trauma patient with displaced fractures of the left lateral sixth to ninth ribs. Tables list types of injuries, NEXUS chest decision instrument imaging criteria, level 2 evidence-based recommendations for the management of pulmonary contusion and flail chest by the Eastern Association for the Surgery of Trauma, Eastern Association for the Surgery of Trauma practice guidelines for managing issues with pulmonary contusion and flail chest, and the Vancouver simplified and University of Washington grading systems for blunt aortic injury. This review contains 2 videos, 4 highly rendered figures, 10 tables, and 94 references.
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) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".