Tactile sensitivity in the rat: a correlation between receptor structure and function
Bibliographic record
Abstract
Single cutaneous fibers were recorded in the median nerve of the deeply anesthetized rat and the receptor morphology in the forelimb glabrous skin was analyzed to establish a probable correlation between receptor anatomy and physiology. Receptor complexes in the glabrous skin of the rat forelimb were stained immunologically with antibodies NF-200 and PGP-9.5, confirming the presence of Meissner corpuscles and Merkel complexes within the dermal papilla similar to other mammals including primates. Both the Meissner corpuscles and Merkel cell complexes were sparse and located in the pyramidal-shaped palmer pads and the apex of the digit extremities. They were almost totally absent elsewhere in the glabrous skin. No Ruffini receptors or Pacinian corpuscles were found in our samples. A total of 92 cutaneous fibers were retained long enough for analysis. Thirty-five (38%) were characterized as rapidly adapting fibers (RA) and 57 (62%) were slowly adapting afferents (SA). Despite the very limited number of receptors at the tip of the digit, RA receptors outnumbered SA fibers 3.2/1.0. In contrast, SA fibers on the thenar pad outnumbered RA receptors by a ratio of 3-1. Despite the very limited number of low threshold mechanoreceptors in the glabrous skin of the rat forelimb, the prevalence of SA afferents in the palm and more frequent occurrence of RA afferents in the digit extremity suggest differences in functionality both for locomotion and object manipulation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".