Models of Neuropathic Pain in the Rat
Bibliographic record
Abstract
Peripheral nerve injury due to trauma, disease, and certain toxins sometimes produces abnormal (neuropathic) pain syndromes that are chronic and refractory to standard analgesics. Knowledge of the mechanisms that produce neuropathic pain and the ability to search for new drugs to control it have been greatly advanced by the introduction of rat models of post-traumatic painful peripheral neuropathy. There are currently three models of neuropathic pain in the rat that are widely used. The procedures to create these models and the behavioral assays used to quantify the resulting neuropathic pain symptoms are described in this unit: the chronic constriction injury (CCI) model, the partial sciatic ligation (PSL) model, and the spinal nerve ligation (SNL) model. Four kinds of abnormal pain sensations are commonly measured to assess the outcome: heat-hyperalgesia, mechano-hyperalgesia, mechano-allodynia, and cold-allodynia.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".