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Record W4290839932 · doi:10.1097/md.0000000000028678

Effectiveness of acupuncture in postpartum depression: A protocol for an overview of systematic reviews

2022· article· en· W4290839932 on OpenAlexaff
Fan Bu, Yonghou Zhao, Jianbo Chai, Wanyu Wang

Bibliographic record

VenueMedicine · 2022
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsMedicineSystematic reviewProtocol (science)Data extractionMEDLINEAcupunctureCochrane LibraryEvidence-based medicinePostpartum depressionContext (archaeology)Grading (engineering)Alternative medicineMeta-analysisMedical physicsPathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Since conflicting evidence from systematic reviews and meta-analyses (SRs/MAs) on the effectiveness of acupuncture in the treatment of postpartum depression is observed. To systematically collate, appraise and synthesize the evidence from these SRs/MAs, an overview will be performed, and this study is an overview protocol. METHODS AND ANALYSIS: Eight databases will be searched: Medicine, Web of science, Cochrane Library, Embase, China National Knowledge Infrastructure, SinoMed, VIP, and Wanfang Data. SRs/MAs of acupuncture on postpartum depression will be included. Literature screening, data extraction, and evaluation of the review quality will be performed by 2 independent reviewers. The methodological quality, reporting quality, and evidence quality will be assessed using the assessment of multiple systematic reviews-2 tool, the preferred reporting items for systematic reviews and meta-analyses checklists, and the grading of recommendations, assessment, development, and evaluation system, respectively. The results will be presented in the context of the topic and the objects of the overview. This study will help bridge the implementation gap between clinical evidence and its translation in clinical application, identify flaws in research and guide future high-quality study.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.366
Threshold uncertainty score0.365

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.165
GPT teacher head0.452
Teacher spread0.287 · 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 designSystematic review
Domainnot available
GenreProtocol

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

Citations8
Published2022
Admission routes1
Has abstractyes

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