Bibliographic record
Abstract
OBJECTIVES: To review the success of non-surgical management, which included antibiotics and a single thoracocentesis, in 15 dogs presenting with pyothorax. METHODS: Sixteen dogs were selected retrospectively from case files at the Veterinary Cardiorespiratory Centre. RESULTS: One dog was diagnosed with a mass suspected to be a pulmonary abscess on ultrasound examination and was referred for surgery. Fifteen dogs were treated medically. Springer spaniels were the most commonly presented breed (six cases) followed by Labrador retrievers (three cases). Under sedation or general anaesthesia, thoracocentesis was performed unilaterally and as much purulent effusion as possible was removed. Lavage of the thorax was not undertaken. In most dogs, antibiotic treatment was ampicillin at a mean dose of 33 mg/kg administered three times daily and 25 mg/kg metronidazole administered twice daily. Antibiotics were provided for a minimum of six weeks. All dogs recovered completely and did not show relapse on prolonged follow-up. This included one dog, which had very widespread pleural adhesions and minimal effusion. CLINICAL SIGNIFICANCE: In dogs that do not have evidence of pulmonary masses or consolidations and no evidence of granular pleural effusion, medical therapy may be curative even in chronic cases of pyothorax with pleural adhesions.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".