The Physiology, Pharmacology and Therapeutic Manipulation of the Internal Anal Sphincter
Bibliographic record
Abstract
Recent research into the physiology and pharmacology of the internal anal sphincter has elucidated the importance of this structure in health and disease. Its pharmacological manipulation for therapeutic gain has focused mainly on agents to reduce internal anal sphincter tone, a 'chemical sphincterotomy' that might heal chronic anal fissure. However, drugs to increase sphincter tone, and augment intermittent and appropriate relaxation are also being evaluated. The initial results with this medical approach to anorectal disease have often been disappointing, failing to match the results achievable with surgery, and many of these drugs have a high rate of side effects in the short term. However, clinical trials have yet to establish the optimum doses, dose intervals and routes of administration for many of these therapies. Furthermore, it is uncertain whether this medical approach should be applied to all patients or just to an as yet undefined subgroup. Certainly, even in the current environment of uncertainty, there is little reason not to try medical manipulation of the internal sphincter as first-line treatment. Surgery remains an option for treatment failures; patients responding to pharmacological manipulation of the internal anal sphincter are spared the long term risks of continence that are inherent in many surgical procedures on the anorectum.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".