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An introduction and analysis of current situation of Canadian acupuncture standards

2012· article· en· W3029202576 on OpenAlexaboutno aff
Jiajia Liu, Yi Yang, Yi Guo, Guilan Li, Zhankui Wang, Zixu Wang, Xuan Zhang

Bibliographic record

VenueTraditional Chinese Medicine · 2012
Typearticle
Languageen
FieldMedicine
TopicHealthcare and Venom Research
Canadian institutionsnot available
Fundersnot available
KeywordsStandardizationPublicityAcupunctureCorporationMedicineAdministration (probate law)BusinessTechnical standardInternational standardizationAlternative medicinePublic relationsPublic administrationPolitical scienceFinanceMarketingLawPathology

Abstract

fetched live from OpenAlex

The standardization of acupuncture and moxibustion in Canada is increasingly flouring nowadays:on one hand,acupuncture industry in legislated provinces is in the charge of direct administrative departments and associations of acu-moxi; on the other hand,according to the local situations,relevant regulations have been made,which are concentrated on two aspects-technical and administrative standards.Undoubtedly,Canadian Alliance of Regulatory Bodies for TCM Practitioners and Acupuncturist (CARB),united by each provincial TCM/Acupuncture Administration,is the first step to issue federal standards and establish federal level management institution.However,now the releasing of a fundamental regulatory file is in need of active corporation and publicity from each province and association.Therefore,it shows that the body of standardization in Canada is still not relatively perfect.Through introducing and analyzing the relevant information,the author expects that the readers can know the current development of acupuncture and moxibustion standardization in Canada. Key words: Canada; Acupuncture standards; Standardization

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.863
Threshold uncertainty score0.994

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0160.031
Science and technology studies0.0080.002
Scholarly communication0.0070.002
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.098
GPT teacher head0.421
Teacher spread0.323 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations0
Published2012
Admission routes1
Has abstractyes

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