Applying Constitution in Chinese Medicine Questionnaire,designed by WANG Qi(English version) to survey TCM constitutions of the American and Canadian Caucasian in Beijing
Bibliographic record
Abstract
Objective: Applying Constitution in Chinese Medicine Questionnaire,designed by WANG Qi(English version) to preliminary survey the TCM body constitutions of the American and Canadian Caucasian in Beijing,analyzing the formation of characteristics of their body constitutions.Methods: Conducting the survey of Constitution in Chinese Medicine Questionnaire,designed by WANG Qi(English version) on a sample of 400 individuals from 3 universities,clinics and hospitals in Beijing.Evaluate body constitution of each individual by score(Balanced Constitution,Qi-deficient Constitution,Yang-deficient Constitution,Yin-deficient Constitution,Phlegm-dampness Constitution,Damp-heat Constitution,Stagnant Blood Constitution,Stagnant Qi Constitution,and Inherited Special Constitution);identifying TCM constitution by using discriminated analysis,then distinguish by larithmics to understand the distribution of sociodemographic segmentation.Results: Among the common population of the American and Canadian Caucasian in Beijing,51.0% were 'Balanced Constitution' while the rest of the 49.0% were identified as one of the 'Unbalanced Constitution'.The top three 'Unbalanced Constitution' were Yang-deficient Constitution,Qi-deficient Constitution,and Inherited Special Constitution,which counted for 13.6%,9.6% and 6.1%,respectively.The ratio of each body constitution in TCM was different by gender,age,marital status,occupation and educational background.Conclusion: As the result,we found that showed different characteristics of TCM body constitution by the distribution of sociodemographic segmentation in the American and Canadian Caucasian in Beijing with the common population of Chinese.The TCM health recommendations should be guided by the types of TCM body constitution.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".