Traumatic lung injury attributed to tornadic activity–induced barometric pressure changes in two dogs
Bibliographic record
Abstract
CASE DESCRIPTION A 7-year-old castrated male Italian Greyhound (dog 1) and an approximately 1-year-old female Labrador Retriever (dog 2) were evaluated because of respiratory distress 8 and 10 days, respectively, after a tornado. CLINICAL FINDINGS No obvious external injuries were identified auscultation revealed decreased bronchovesicular sounds in the affected hemithorax of both dogs. Clinicopathologic changes were mild, with evidence of inflammation in both dogs. Thoracic radiography of both dogs revealed pneumothorax and pleural effusion with effacement of the diaphragm; findings on CT included severe pulmonary atelectasis of affected lung lobes with normal bronchial tree configurtion and no evidence of diaphragmatic hernia. TREATMENT AND OUTCOME Exploratory thoracotomy of both dogs confirmed CT findings Pulmonary parenchymal damage consistent with a large rupture was found in both patients. A large hematoma was adhered to the ruptured lung lobe of dog 1. Grossly affected lung tissue was removed; histologic examination revealed atelectasis, pulmonary fib osis, thrombosis, and minimal (dog 1) to marked (dog 2) inflammation Microbial culture of lung tissue yielded no growth for dog 1 and Streptococcus spp and Escherichia coli susceptible to amoxicillin-clavulanic acid for dog 2. Dog 1 had a recurrence of pneumothorax treated by drainage with a thoracostomy tube 1 month after surgery. Eighteen months after surgery, both dogs were reportedly doing well. CLINICAL RELEVANCE Development of clinical signs after a tornado, together with clinical, diagnostic imaging, surgical, and histologic findings led to a presumptive diagnosis of pulmonary barotrauma for both dogs. Long-term outcome for these dogs, treated at a referral hospital, was good.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".