Suggestion on Locating Method for ST36 Acupoint Based on Neuroanatomical Features
Bibliographic record
Abstract
Objectives : There are many variations in the ST36 acupoint location.The purpose of this article is to suggest a method of locating the ST36 acupoint.Methods : Based on the available research and the neuroanatomical characteristics of the underlying acupoint, we summarized the proper procedure for finding the ST36 acupoint.Results : ST36 is 3 B-cun inferior to ST35 and is vertically situated on the line that connects ST35 and ST41.The ST36 acupoint corresponds to the deep peroneal nerve, which is situated in the tibialis anterior muscle's back.The neurovascular bundles that are located on the interosseous membrane between the interosseous crests of the tibia and fibula include the deep peroneal nerve, anterior tibial artery, and anterior tibial vein.According to both classical and modern literature, this acupoint can be found horizontally between the two muscles, tibialis anterior and extensor digitorum longus.Conclusions : Based on a review of the literature and neuroanatomical features, we suggest that ST36 can be positioned horizontally between tibialis anterior and extensor digitorum longus.Additional imaging studies and clinical proof are required to determine ST36 acupoint.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".