Intra‐ and inter‐rater agreement for the detection of band neutrophils and toxic change in horses
Bibliographic record
Abstract
BACKGROUND: The detection of band neutrophils and toxic change via microscopic blood smear review is vitally important, as their presence indicates systemic inflammation. However, in-clinic evaluation of WBC morphology is often limited. OBJECTIVE: We aimed to determine the agreement between expert raters in the detection of bands and toxic change. METHODS: Three board-certified clinical pathologists each evaluated 109 blood smears from horses with acute disease, and 19 control smears from healthy horses. The pathologists determined if bands were present, and if so, the percentage of bands present. They also determined if toxic change was present, and if so, the grade of toxic change. Intra-rater agreement was evaluated using 12 duplicate blood smears. Agreement on the presence of bands between pathologists and an in-clinic hematology analyzer was evaluated. RESULTS: Intra-rater agreement was substantial to almost perfect. Agreement between pathologists for the detection of bands was moderate, but when pathologists agreed bands were present, there was excellent agreement on the percentage of bands and mature neutrophils. Agreement between pathologists for the detection of high-grade, clinically relevant toxic change was fair. When pathologists agreed high-grade toxic change was present, there was fair agreement on Döhle bodies and cytoplasmic basophilia and poor agreement on cytoplasmic vacuolation. Agreement between individual pathologists and the in-clinic hematology analyzer for the indication of bands was fair to moderate. CONCLUSIONS: Consistent identification of bands and toxic change is challenging, even for highly trained personnel. It is, thus,not surprising that in-clinic blood smear evaluation of WBC morphology by non-experts could be inadequate.
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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 | 0.081 | 0.103 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".