Current Status and Future Prospects of Acupuncture and Traditional Chinese Medicine in Canada
Bibliographic record
Abstract
自从 1970 年代，繁体中文药(TCM ) 和针灸被主流的社会逐渐地接受了并且很快一直在膨胀，伴随自从 1980 年代的中国移民的潮。针灸立法被 5 个省的政府在在 1988 和 2014 之间的加拿大同意了。在自动调节的接受以后， 5 所相应学院一个接一个被建立。道德规范和职业实践标准被学院开发。不列颠哥伦比亚(BC ) 成为了第一个加拿大的省为它在 2008 开始的医疗服务计划奖赏帮助接受者作为一个增补好处提供针灸处理。5 所学院联合起来在一样的年里形成繁体中文药专业人员和针灸医生(CARBTCMPA ) 的规章的身体的加拿大的联盟。为在加拿大的 TCM 的实践的入口级的职业才能被 CARB-TCMPA 在 2010 开发。为针灸医生，草药医生和 TCM 专业人员的平底锅加拿大人登记考试后来被管理了并且安排 2013。为 TCM 的医生的入口级的职业才能被繁体中文药专业人员的学院和不列颠哥伦比亚(CTCMA-BC ) 的针灸医生在 2014 开发。它在加拿大为 TCM 职业的未来开发勾略蓝图。
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".