Correlation between severity of clinical signs and motor evoked potentials after transcranial magnetic stimulation in large-breed dogs with cervical spinal cord disease
Bibliographic record
Abstract
OBJECTIVE: To evaluate use of transcranial magnetic motor evoked potentials for assessment of the functional integrity of the cervical spinal cord in large-breed dogs with cervical spinal cord disease. DESIGN: Randomized, controlled, masked study. ANIMALS: 10 healthy large-breed control dogs and 25 large-breed dogs with cervical spinal cord diseases. PROCEDURE: Affected dogs were allocated to 3 groups on the basis of neurologic status: signs of neck pain alone, ambulatory with ataxia in all limbs, or nonambulatory. Transcranial magnetic stimulation was performed on each dog with the same standard technique. Motor evoked potentials (MEP) were recorded from electrodes inserted in the tibialis cranialis muscle. Following the procedure, each dog was anesthetized and cervical radiography, CSF analysis, and cervical myelography were performed. The MEP latencies and amplitudes were correlated with neurologic status of the dogs after correction for neuronal path length. RESULTS: Mean MEP latencies and amplitudes were significantly different between control dogs and dogs in each of the 3 neurologic categories, but were not significantly different among dogs in the 3 neurologic categories. A linear association was evident between MEP latencies and amplitudes and severity of neurologic deficits; the more severe the neurologic deficits, the more prolonged the latencies and the more decreased the amplitudes. CONCLUSIONS AND CLINICAL RELEVANCE: Transcranial magnetic MEP are useful to assess severity of cervical spinal cord disease in large-breed dogs. Impairment of the functional integrity of the cervical spinal cord was found even in dogs with neck pain alone.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".