MétaCan
Menu
Back to cohort
Record W4402146094 · doi:10.1093/aje/kwae332

Assessing the certainty of the evidence in systematic reviews: importance, process, and use

2024· article· en· W4402146094 on OpenAlexaff
Romina Brignardello‐Petersen, Gordon H Guyatt

Bibliographic record

VenueAmerican Journal of Epidemiology · 2024
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsMcMaster UniversityImpact
Fundersnot available
KeywordsCertaintySystematic reviewProcess (computing)MedicineSystematic processMEDLINERisk analysis (engineering)Computer scienceEpistemologyEngineeringPolitical sciencePhilosophyWork in processOperations managementLaw

Abstract

fetched live from OpenAlex

When interpreting results and drawing conclusions, authors of systematic reviews should consider the limitations of the evidence included in their review. The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach provides a framework for the explicit consideration of the limitations of the evidence included in a systematic review, and for incorporating this assessment into the conclusions. Assessments of certainty of evidence are a methodological expectation of systematic reviews. The certainty of the evidence is specific to each outcome in a systematic review and can be rated as high, moderate, low, or very low. Because it will have an important impact, before assessing the certainty of evidence, reviewers must clarify the intent of their question: are they interested in causation or association. Serious concerns regarding limitations in the study design, inconsistency, imprecision, indirectness, and publication bias can decrease the certainty of the evidence. Using an example, this article describes and illustrates the importance and the steps for assessing the certainty of evidence and drawing accurate conclusions in a systematic review.

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)0.402
metaresearch head score (Gemma)0.572
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.4020.572
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
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 head0.790
GPT teacher head0.604
Teacher spread0.187 · 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 designObservational
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

Citations40
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of EpidemiologySame topicMeta-analysis and systematic reviewsFrench-language works237,207