Laboratory blood analysis in Strigiformes—Part I: hematologic reference intervals and agreement between manual blood cell counting techniques
Bibliographic record
Abstract
BACKGROUND: While hematologic reference intervals (RI) are available for multiple raptorial species of the order Accipitriformes and Falconiformes, there is a lack of valuable hematologic information in Strigiformes that can be used for diagnostic and health monitoring purposes. OBJECTIVES: The objective was to report RI in Strigiformes for hematologic variables and to assess agreement between manual cell counting techniques. METHODS: A multi-center prospective study was designed to assess hematologic RI and blood cell morphology in owl species. Samples were collected from individuals representing 13 Strigiformes species, including Great Horned Owl, Snowy Owl, Eurasian Eagle Owl, Barred Owl, Great Gray Owl, Ural Owl, Northern Saw-Whet Owls, Northern Hawk Owl, Spectacled Owl, Barn Owl, Eastern Screech Owl, Long-Eared Owl, and Short-Eared Owl. Red blood cell count was determined manually using a hemocytometer. White blood cell count was determined using 3 manual counting techniques: (1) phloxine B technique, (2) Natt and Herrick technique, and (3) estimation from the smear. Differential counts and blood cell morphology were determined on smears. Reference intervals were determined and agreement between methods was calculated. RESULTS: Important species-specific differences were observed in blood cell counts and granulocyte morphology. Differences in WBC count between species did not appear to be predictable based on phylogenetic relationships. Overall, most boreal owl species exhibited a lower WBC count than other species. Important disagreements were found between different manual WBC counting techniques. CONCLUSIONS: Disagreements observed between manual counting techniques suggest that technique-specific RI should be used in Strigiformes.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".