Accuracy, intermethod agreement, and inter-reviewer agreement for use of magnetic resonance imaging and myelography in small-breed dogs with naturally occurring first-time intervertebral disk extrusion
Bibliographic record
Abstract
OBJECTIVE: To determine accuracy, intermethod agreement, and inter-reviewer agreement for multisequence magnetic resonance imaging (MRI) and 2-view orthogonal myelography in small-breed dogs with first-time intervertebral disk (IVD) extrusion. DESIGN: Prospective evaluation study. ANIMALS: 24 dogs with thoracolumbar IVD extrusion. PROCEDURES: Each dog underwent MRI and myelography. Images obtained with each modality were independently evaluated and assigned standardized scores in a blinded manner by 3 reviewers. Results were compared with surgical findings. Inter-reviewer and intermethod agreements were assessed via κ statistics. Accuracy was assessed as the percentage of dogs for which ≥ 2 of 3 reviewers recorded findings identical to those determined surgically. RESULTS: Inter-reviewer agreement was substantial for site (κ = 0.70) and side of IVD extrusion (κ = 0.62) in T2-weighted magnetic resonance images and was substantial for site (κ = 0.72) and fair for side of extrusion (κ = 0.37) in myelographic images. Agreement for site between each modality and surgical findings was near perfect (κ = 0.94 and 0.88 for MRI and myelography, respectively). Intermethod agreement was substantial for site (κ = 0.71) and moderate for side of extrusion (κ = 0.40). Accuracy of MRI for site and side was 100% when results for T1-weighted, T2-weighted, and contrast-enhanced T1-weighted sequences were combined. Accuracy of myelography was 90.9% and 54.5% for site and side, respectively. CONCLUSIONS AND CLINICAL RELEVANCE: Agreement between imaging results and surgical findings for identification of IVD extrusion sites in small-breed dogs was similar for MRI and myelography. However, MRI appeared to be more accurate than myelography and allowed evaluation of extradural compressive mass composition.
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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 | 0.176 | 0.311 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| 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".