Bibliographic record
Abstract
Abstract Peripheral neuropathic pain is the most debilitating of all clinical pain syndromes and affects a large and growing number of people worldwide. There are diverse causes for peripheral neuropathic pain, which may be experienced after traumatic nerve injury or from diseases that affect peripheral nerves, such as diabetes, HIV/AIDS, and cancer, and it can also result from toxic chemicals, such as cancer chemotherapy agents. Despite these varying causes, it is clear that neuropathic pain is due to persistent pathological alterations resulting in hyperexcitability in the peripheral and central nervous systems, and it is the neuropathology that must be targeted for effective therapy of which there is none presently available. Mechanistically, neuropathic pain is distinct from acute pain and inflammatory pain, for which many effective therapies are known. In this review, we describe the relationships between clinical symptoms and experimental models of peripheral neuropathic pain, and we provide a framework for understanding the potential mechanisms that involve primary neuronal dysfunction as well as pathological changes in neuron‐glial signaling. Drug Dev. Res. 67:289–301, 2006. © 2006 Wiley‐Liss, Inc.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".