Sensory profile of cats with potential pain‐related diabetic neuropathy
Bibliographic record
Abstract
Abstract Background Diabetes mellitus (DM) can cause peripheral neuropathy. This study aimed to evaluate sensory function by measuring the mechanical nociceptive thresholds (MNT) and diffuse noxious inhibitory control (DNIC) of cats with diabetes mellitus (DM cats ). Methods Eight cats with DM and 12 healthy controls were included in a prospective, randomised study. MNT were measured by applying pressure against the metatarsal pad (MNT bio ). MNT were also measured using a mechanical actuator attached to one of the cat's pelvic limbs (MNT top ). The DNIC was assessed by comparing MNT top before and after a conditioning stimulus. Results MNT bio of the controls were significantly lower (2.1 ± 0.7 N) than those of DM cats (3.6 ± 1.2 N). DNIC and MNT top were not different between groups. Limitations This study had a small cohort of patients and an MNT cut‐off to prevent injuries. Conclusion DM cats showed hypoalgesia and loss of sensory function. This study could not differentiate DNIC between healthy and those with DM.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".