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Record W2187509941 · doi:10.1089/acu.2014.1040

Standardized Ear Acupuncture Nomenclature Utilizing Auricular Landmarks and 3-D Graphic Imaging for Delineating Different Auricular Zones

2014· article· en· W2187509941 on OpenAlexaff
Terry Oleson

Bibliographic record

VenueMedical Acupuncture · 2014
Typearticle
Languageen
FieldMedicine
TopicMedical and Biological Sciences
Canadian institutions123 Certification (Canada)
Fundersnot available
KeywordsMedicineAuricleAcupunctureTerminologyPinnaAnatomyPathologyLinguistics

Abstract

fetched live from OpenAlex

Background: The World Health Organization (WHO) has actively sought to bring international standardization of the terminology used in acupuncture texts, training, and research. Objectives: The purpose of the present article is to delineate specific auricular landmarks that can be utilized to differentiate one auricular zone from another, thus facilitating international communication regarding the specific, somatotopic location of different parts of the body on the external ear. Methods: Two-dimensional ear diagrams and photographs of actual ears were utilized to develop a detailed, three dimensional (3-D) image of the external ear. These 3-D images were then used to show the specific locations of auricular landmarks and auricular zones in both the American and Chinese systems for representing the somatotopic locations of different body areas. Results: 3-D images of the auricle were created that were able to depict the specific locations of auricular landmarks and auricular zones in both the American and Chinese zone systems. Conclusions: Distinctive auricular landmarks were identified and depicted on two-dimensional and 3-D images of the external ear. These landmarks allowed the comparison of an American auricular zone system to a standardized Chinese auricular zone system.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.697
Threshold uncertainty score0.876

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.010
GPT teacher head0.262
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2014
Admission routes1
Has abstractyes

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