Accuracy of selected neurological clinical tests in diagnosing <scp>MRI</scp>‐detectable forebrain lesion in dogs
Why this work is in the frame
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Bibliographic record
Abstract
This retrospective case study aims to evaluate the accuracy of menace response, response to nasal stimulation and proprioceptive placing in diagnosing forebrain lesion in dogs. A total of 145 client-owned dogs investigated by magnetic resonance imaging study of the brain between December 2017 and June 2019 were evaluated. Seventy-one dogs with no magnetic resonance imaging-detectable intracranial and significant cerebrospinal fluid abnormality or recent history of seizure (<48 h) served as controls. Binary regression analysis was performed to determine the sensitivity, specificity and likelihood ratios of each selected test. Older age at presentation was a significant risk factor for the presence of a forebrain lesion. Menace (62.5%) and proprioceptive deficits (40.5%) were common findings in all dogs. They were also significantly associated with the presence of forebrain abnormality. Moreover, they were more sensitive (77.3% and 82.2%, respectively) and specific (50.0% and 62.5%, respectively) when applied to dogs aged 6 years or older. Nonetheless, all of these tests' likelihood ratios, and thus reliability are poor. These neurological tests are commonly employed for diagnosing forebrain disease in dogs, yet are not highly accurate in diagnosing forebrain abnormality. Clinicians should interpret these clinical test results along with the patient history when designing a diagnostic plan.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it