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Record W2520830026 · doi:10.4103/0019-5049.190628

A brief overview of systematic reviews and meta-analyses

2016· review· en· W2520830026 on OpenAlexaff
Kamath Sriganesh, Harsha Shanthanna, Jason W. Busse

Bibliographic record

VenueIndian Journal of Anaesthesia · 2016
Typereview
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineSystematic reviewMeta-analysisPoolingCritical appraisalMEDLINEBest evidenceEvidence-based medicineMedical physicsIntensive care medicineAlternative medicinePathologyArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Systematic reviews (SRs) are performed to acquire all evidence to address a specific clinical question and involve a reproducible and thorough search of the literature and critical appraisal of eligible studies. When combined with a meta-analysis (quantitatively pooling of results of individual studies), a rigorously conducted SR provides the best available evidence for informing clinical practice. In this article, we provide a brief overview of SRs and meta-analyses for anaesthesiologists.

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)0.226
metaresearch head score (Gemma)0.061
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad), Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Meta-epidemiology (broad), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.790
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2260.061
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0710.031
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0050.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.908
GPT teacher head0.599
Teacher spread0.309 · 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; both teacher heads agree on what is shown here.

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

Citations38
Published2016
Admission routes1
Has abstractyes

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