Comparison of bronchoalveolar lavage fluid obtained by manual aspiration with a handheld syringe with that obtained by automated suction pump aspiration from healthy dogs
Bibliographic record
Abstract
OBJECTIVE: To compare bronchoalveolar lavage (BAL) fluid obtained by manual aspiration (MA) with a handheld syringe with that obtained by suction pump aspiration (SPA) in healthy dogs. ANIMALS: 13 adult Beagles. PROCEDURES: Each dog was anesthetized and bronchoscopic BAL was performed. The MA technique was accomplished with a 35-mL syringe attached to the bronchoscope biopsy channel. The SPA technique was achieved with negative pressure (5 kPa) applied to the bronchoscope suction valve with a disposable suction trap. Both aspiration techniques were performed in each dog in randomized order on opposite caudal lung lobes. Two 1 mL/kg aliquots of warm saline (0.9% NaCl) solution were infused per site. For each BAL fluid sample, the percentage of retrieved fluid was calculated, the total nucleated cell count (TNCC) and differential cell count were determined, and semiquantitative assessment of slide quality was performed. Comparisons were made between MA and SPA techniques for each outcome. RESULTS: 1 dog was removed from the study because of illness. The mean percentage of fluid retrieved (mean difference, 23%) and median TNCC (median distribution of differences, 100 cells/μL) for samples obtained by SPA were significantly greater than those for samples obtained by MA. CONCLUSIONS AND CLINICAL RELEVANCE: In healthy dogs, BAL by SPA resulted in a significantly higher percentage of fluid retrieval and samples with a higher TNCC than did MA. Further evaluation of aspiration techniques in dogs with respiratory tract disease is required to assess whether SPA improves the diagnostic yield of BAL samples.
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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) | 0.000 | 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 | 0.000 | 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".