The human cervix: Comprehensive review of innervation and clinical significance
Bibliographic record
Abstract
Detailed knowledge regarding the innervation and histology of the human cervix is crucial given the surgical removal of this tissue for conditions such as cervical dysplasia. Recent evidence implicates the cervix in the sexual response, making it pertinent to characterize this region to elucidate its role. Despite this, literature describing the overall innervation of the cervix from anatomical and histological perspectives is lacking. The aim of this review was to consolidate descriptions pertaining to human cervix innervation and discuss possible mechanisms of dysfunction, as an unintended result of cervix removal. A detailed literature search of relevant articles describing human cervix innervation was conducted. 1597 articles were screened based on the keywords searched. Only 16 articles, containing information regarding specific evidence of the innervation of the human cervix, were included and categorized based on parameters of innervation (method, type, location). The published evidence demonstrates that the human cervix has sympathetic, parasympathetic, and sensory innervation, but does not characterize changes after surgical procedures. Despite the gaps in knowledge, it is relevant that associations linking clinical procedures, involving cervical removal and adverse sexual health outcomes, become an important focus for discussions between physicians and patients. Future work is needed to better detail the affected innervation as well as the neural pathway-specific relationship to symptoms of sexual dysfunction.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".