{"id":"W4318973081","doi":"10.1136/bmjebm-2022-112053","title":"Different meta-analysis methods can change judgements about imprecision of effect estimates: a meta-epidemiological study","year":2023,"lang":"en","type":"review","venue":"BMJ evidence-based medicine","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Impact","funders":"","keywords":"Meta-analysis; Statistics; Random effects model; Mathematics; Medicine; Restricted maximum likelihood; Maximum likelihood; Econometrics; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["metaresearch","metaepi_broad","metaepi_narrow"],"domain":"methods","study_design":"systematic_review","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"medium","status":"direct model label, unvalidated"},{"model":"gpt","categories":["metaresearch","metaepi_narrow","metaepi_broad"],"domain":"methods","study_design":"meta_analysis","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","metaepi_broad","open_science","insufficient_payload"],"consensus_categories":["metaresearch","metaepi_narrow","metaepi_broad","insufficient_payload"],"category_scores_codex":[0.6144974,0.003642757,0.1512528,0.006392405,0.0002824329,0.0003842319,0.008078281,0.0007782417,0.03555686],"category_scores_gemma":[0.536687,0.001118133,0.07427885,0.0168604,0.0004931893,0.0002986594,0.001113968,0.001148717,0.0009962902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002750828,"about_ca_system_score_gemma":0.0003508826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006465082,"about_ca_topic_score_gemma":0.0002507571,"domain_scores_codex":[0.6700647,0.2484504,0.05377088,0.006069376,0.02036029,0.001284344],"domain_scores_gemma":[0.6266546,0.3138774,0.04061433,0.01524002,0.002658684,0.0009549544],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.00003525776,0.0003082722,0.0009351403,0.01305675,0.610729,0.00008756603,0.0001970974,0.00006026426,5.269549e-7,0.0000292776,0.01122006,0.3633407],"study_design_scores_gemma":[0.0003803852,0.001572929,0.0006170247,0.005560864,0.8966656,0.000006883195,0.0001104045,0.001438823,0.000001173906,0.000353586,0.09257792,0.0007144275],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00002647937,0.941686,0.03555174,0.001298298,0.0008834205,0.02025403,0.0001937537,0.00005173471,0.00005459706],"genre_scores_gemma":[0.0002460588,0.964655,0.01114032,0.0007026578,0.000682681,0.01978834,0.00023435,0.0001440458,0.002406525],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.3626263,"threshold_uncertainty_score":0.9997815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9820049695252123,"score_gpt":0.7362051535903333,"score_spread":0.245799815934879,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}