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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 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)0.020
metaresearch head score (Gemma)0.065
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.065
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0080.013
Bibliometrics0.0240.018
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0100.002

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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
DomainMethods
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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