{"id":"W3009456404","doi":"10.1002/jrsm.1405","title":"Multivariate network meta‐analysis of survival function parameters","year":2020,"lang":"en","type":"article","venue":"Research Synthesis Methods","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Precision Nanosystems (Canada)","funders":"","keywords":"Multivariate statistics; Multivariate analysis; Meta-analysis; Computer science; Function (biology); Statistics; Survival analysis; Econometrics; Mathematics; Medicine; Internal medicine; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_broad","insufficient_payload"],"consensus_categories":["metaresearch","insufficient_payload"],"category_scores_codex":[0.5711988,0.0003617424,0.01120538,0.00135933,0.0002698605,0.0006303453,0.002806758,0.0001638363,0.02938483],"category_scores_gemma":[0.3667572,0.0001769913,0.0102258,0.01769404,0.0002236975,0.0002339963,0.0004524371,0.0004517016,0.0009108459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003229313,"about_ca_system_score_gemma":0.0001022633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001292659,"about_ca_topic_score_gemma":0.00002431514,"domain_scores_codex":[0.6732749,0.2997704,0.01024211,0.002150431,0.01366444,0.0008976846],"domain_scores_gemma":[0.6832762,0.3001426,0.004853985,0.006644482,0.004236319,0.0008463939],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002481912,0.0001958918,0.005607395,0.0001952278,0.7073,0.00001029794,0.001216502,0.05827556,0.004778674,0.0103996,0.02310645,0.1886662],"study_design_scores_gemma":[0.0001622506,0.0001948394,0.01314601,0.00001529943,0.3827654,7.19168e-7,0.001869206,0.4900999,0.003086316,0.01304593,0.09505379,0.0005603436],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002734364,0.003032588,0.981692,0.002955255,0.0001911683,0.0008007906,0.00004045395,0.00001433894,0.008539071],"genre_scores_gemma":[0.2883737,0.0000732798,0.7091226,0.0002387277,0.0001591795,0.0002355237,0.000005732592,0.00003425854,0.001757018],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4318244,"threshold_uncertainty_score":0.9998671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9714935275619198,"score_gpt":0.6950105413173112,"score_spread":0.2764829862446085,"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."}}