Neuroembryology of the Acupuncture Principal Meridians: Part 3. The Head and Neck
Bibliographic record
Abstract
Background: Accumulating evidence from anatomical, physiologic, and neuroimaging research shows that Classical acupuncture points stimulate nerve trunks or their branches in the head, trunk, and extremities. The first part of this series revealed that phenomenon in the extremities. Principal meridian distributions mirror those of major peripheral nerves there and Classical acupuncture points are proximate to peripheral nerves there. These relationships were shown to be consistent with the linear neuroembryologic development of the extremities. The second part of this series revealed that, in the trunk, a neuroanatomical basis for the Principal meridians exists consistent with lateral folding in early fetal neuroembryologic development. Objective: The aim of this Part is to provide anatomical data that corroborates a neuroanatomical basis for the Principal meridians in the head and neck, which is consistent with the longitudinal and lateral folding that occurs in early fetal neuroembryologic development. Methods: Adobe Photoshop software was used to apply Classical acupuncture points and Principal meridians as layers superimposed on neuroanatomic images of the head and neck, allowing demonstration of their anatomical relationships. Results: The Principal meridian distributions in the head and region can be conceptualized as connecting branches of the cranial and/or cervical spinal nerves. Conclusions: Anatomical data support the conceptualization of acupuncture Principal meridians in the head and neck as connecting branches of the cranial and/or cervical spinal nerves and are consistent with neuroembryologic development. Overall, the acupuncture Principal meridians can be conceptualized to have a neuroanatomical substrate that is corroborated by developmental neuroembryology.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".