Evaluation of laboratory methods to improve characterization of dogs with von Willebrand disease.
Bibliographic record
Abstract
The objective of the study was to investigate the value of additional tests [platelet count, partial thromboplastin time (PTT), platelet function analysis using the PFA-100, Collagen binding assay (vWF:CBA), and Factor VIII activity], for use in conjunction with the von Willebrand factor antigen enzyme-linked immunosorbent assay (ELISA), as part of a newly developed diagnostic profile for improved characterization of patients with von Willebrand disease (vWD). The study population included 183 clinically healthy canines ranging in vWF:Ag concentration from 1% to 125%. The Asserachrom vWF:Ag ELISA assay was used as an external control for the determination of vWD status. Degree of association between the additional tests and vWF concentration was evaluated, and associations between the additional tests were also assessed, including their ability to distinguish dogs with vWD from those without vWD. In addition, a reference interval was determined for the PFA-100 platelet function analyzer. Strong associations were found between the PFA-100, vWF:CBA, and Asserachrom vWF:Ag assay, and a significant association was found between the PFA-100 and vWF:CBA. An association was detected between Factor VIII activity and the Asserachrom vWF:Ag assay, the vWF:CBA and the PFA-100; however, a corresponding pattern was not visually apparent in the raw data, making the association clinically irrelevant. The association between the platelet count and the PTT with the other additional tests was negligible. Based on our results, the vWF:CBA and PFA-100 would be valuable assets, in conjunction with a vWF:Ag assay, in a canine vWD diagnostic profile to further characterize patients with this disease.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".