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[Vascular cognitive impairment with no dementia treated with auricular acupuncture and acupuncture:a randomized controlled trial].

2016· article· en· W3025261780 on OpenAlexaboutno aff
Shuxin Wang, Bin Zhang, Muxi Liao, Xun Zhuang, Zhanqiong Xu, Yunxuan Huang, Lixing Zhuang

Bibliographic record

VenuePubMed · 2016
Typearticle
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsDry needlingMedicineAcupunctureRandomized controlled trialMontreal Cognitive AssessmentDementiaPhysical therapyVascular dementiaSurgeryInternal medicineAlternative medicineDisease

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare the clinical efficacy on vascular cognitive impairment with no dementia (VCIND) between the combined therapy of auricular acupuncture and acupuncture and the simple acupuncture. METHODS: 's three needling therapy was just provided, once a day. The treatment was given for 4 weeks in the two groups. Montreal cognitive assessment (MoCA) and social function activities questionnaire (FAQ) were adopted for the evaluation comparison before treatment and in 2 weeks and 4 weeks after treatment in patients of the two groups. RESULTS: >0.05). CONCLUSIONS: The combined therapy of auricular acupuncture and acupuncture effectively improve the cognitive function and social function, which are better than the effects of simple acupuncture in VCIND. The improvement of the combined therapy in social function is more advantageous in the treatment of the first two weeks.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.005
GPT teacher head0.182
Teacher spread0.177 · 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 designRandomized trial
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
Published2016
Admission routes1
Has abstractyes

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