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Abbreviated and comprehensive literature searches led to identical or very similar effect estimates: a meta-epidemiological study

2020· review· en· W3048211970 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Clinical Epidemiology · 2020
Typereview
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsInstitute of Health EconomicsUniversity of Alberta
Fundersnot available
KeywordsInterquartile rangeMeta-analysisConfidence intervalMedicineOdds ratioMEDLINEEpidemiologyStatisticsSystematic reviewInternal medicineMathematicsBiology

Abstract

fetched live from OpenAlex

OBJECTIVES: The objective of this study was to assess the agreement of treatment effect estimates from meta-analyses based on abbreviated or comprehensive literature searches. STUDY DESIGN AND SETTING: This was a meta-epidemiological study. We abbreviated 47 comprehensive Cochrane review searches and searched MEDLINE/Embase/CENTRAL alone, in combination, with/without checking references (658 new searches). We compared one meta-analysis from each review with recalculated ones based on abbreviated searches. RESULTS: The 47 original meta-analyses included 444 trials (median 6 per review [interquartile range (IQR) 3-11]) with 360045 participants (median 1,371 per review [IQR 685-8,041]). Depending on the search approach, abbreviated searches led to identical effect estimates in 34-79% of meta-analyses, to different effect estimates with the same direction and level of statistical significance in 15-51%, and to opposite effects (or effects could not be estimated anymore) in 6-13%. The deviation of effect sizes was zero in 50% of the meta-analyses and in 75% not larger than 1.07-fold. Effect estimates of abbreviated searches were not consistently smaller or larger (median ratio of odds ratio 1 [IQR 1-1.01]) but more imprecise (1.02-1.06-fold larger standard errors). CONCLUSION: Abbreviated literature searches often led to identical or very similar effect estimates as comprehensive searches with slightly increased confidence intervals. Relevant deviations may occur.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearchMeta-epidemiology (narrow)Meta-epidemiology (broad)
Domain: Methods · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
gptMetaresearchMeta-epidemiology (narrow)Meta-epidemiology (broad)
Domain: Methods · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Meta-analysishigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.657
metaresearch head score (Gemma)0.954
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.818
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.6570.954
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.1810.043
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0050.001
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0030.002

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 head0.966
GPT teacher head0.737
Teacher spread0.228 · 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