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Record W4400853486 · doi:10.1038/s41433-024-03255-2

Exploring the fragility of meta-analyses in ophthalmology: a systematic review

2024· review· en· W4400853486 on OpenAlexaff
Keean Nanji, Jim Shenchu Xie, Amin Hatamnejad, Daiana R. Pur, Mark Phillips, Dena Zeraatkar, Tien Yin Wong, Robyn H. Guymer, Peter K. Kaiser, Sobha Sivaprasad, Mohit Bhandari, David Steel, Charles C. Wykoff, Varun Chaudhary

Bibliographic record

VenueEye · 2024
Typereview
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsWestern UniversityMcMaster UniversityImpact
Fundersnot available
KeywordsMedicineFragilityOptometryOphthalmologyMEDLINENeuro-ophthalmologyMeta-analysisGlaucomaPathologyChemistry

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

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 (broad)
Domain: Methods · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
gptMetaresearch
Domain: Methods · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewmedium
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)0.263
metaresearch head score (Gemma)0.111
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad), Open science, 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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.633
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2630.111
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0600.030
Bibliometrics0.0010.007
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0060.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.007

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 head0.981
GPT teacher head0.681
Teacher spread0.300 · 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

Labeled directly by 2 models reading the full record.

MetaresearchMeta-epidemiology (broad)

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designSystematic review
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

Citations3
Published2024
Admission routes1
Has abstractno

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