Bibliographic record
Abstract
What kind of reception do regenerating axons or SCs encounter when they enter nerve trunks that have not housed axons for substantial periods of time? Are target organs receptive to reactivation after months or years of denervation? Unfortunately, the structural and molecular consequences of prolonged denervation substantially diminish the likelihood for reinnervation. This chapter deals with delayed reinnervation, a common and all too frequently unavoidable problem in patients. Clinical scenarios and long-term denervation There are several reasons why axons may encounter denervated distal stumps or target organs months or years after an injury. The first is obvious. The most optimistic rates of axon recovery range between 1 and 3 mm/day or an inch per month. Many severe human nerve trunk injuries occur in large proximal nerves, such as the sciatic nerve in the thigh or buttock [557] (see Figure 1.2). These lesions rarely allow successful recovery of sensation or motor connections to muscle endplates in the distal leg or foot. In the case of a lesion of the sciatic nerve at the level of the thigh, it would require over a year for axons to regenerate an approximate distance of 800 mm to the foot unimpeded. Moreover, distal portions of the nerve trunk would not receive new axons for many months. This analysis, however, oversimplifies the true scenario that may exist. Estimates of regeneration are based on the time the first axons meet their target, whereas a substantial population of axons must connect to their targets for functional reinnervation.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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".