Interpretation of cerebrospinal fluid analysis from recumbent cows using different thresholds of red blood cell count
Bibliographic record
Abstract
BACKGROUND: Hemodilution of the cerebrospinal fluid (CSF) could confound interpretation of results. Accurately predicting total nucleated cells count (TNCC) and total protein concentration (TPC) attributable to hemodilution is difficult. OBJECTIVE: To determine the effects of hemodilution on TPC and TNCC in bovine CSF. METHODS: Retrospective review of CSF analysis results of downer dairy cows treated at Centre hospitalier universitaire vétérinaire between January 2006 and December 2014. Descriptive statistics were performed using 3 scenarios. RESULTS: Among the 235 samples included, red blood cell (RBC) count (RBCC) ranged from 0 to 869 220 RBC/μL (median = 6.6), TPC ranged from 0.04 to 6.51 g/L (median = 0.27), and TNCC ranged from 0 to 7500 cell/μL (median = 1.1). Among the 157 samples that had <30 RBC/μL (a threshold used in other species), TPC and TNCC varied between 0.13 and 1.06 g/L (median = 0.27) and between 0 and 31.4 cell/μL (median = 0.6), respectively. Eighty-four samples had TPC <0.25 g/L and TNCC ≤4.5 cell/μL. Among those 84 samples, RBCC varied between 0 and 1290 RBC/μL (median = 4.7). In 20 samples, TNCC was 0 with a variation in RBCC between 0 and 840 RBC/μL (median = 3.9). No strong correlations between RBCC and TNCC and TPC were found. CONCLUSIONS: A cutoff around 200 RBC/μL is proposed as clinically meaninful in bovine CSF. Results between 200 and 1290 RBC/μL are equivocal.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".