{"id":"W3043263805","doi":"10.1002/jrsm.1432","title":"Performance of model‐based network meta‐analysis (MBNMA) of time‐course relationships: A simulation study","year":2020,"lang":"en","type":"article","venue":"Research Synthesis Methods","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council; Pfizer UK; Medical Research Council Canada; Department of Health and Social Care; University of Bristol; National Institute for Health and Care Research; University Hospitals Bristol NHS Foundation Trust; Pfizer","keywords":"Pooling; Time point; Robustness (evolution); Computer science; Econometrics; Statistics; Correlation; Covariance; Random effects model; Meta-analysis; Mathematics; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1098265,0.002578025,0.005569634,0.002490069,0.0008442811,0.002483844,0.002842033,0.002768753,0.004972714],"category_scores_gemma":[0.2001603,0.001355038,0.01490153,0.002542462,0.0009091244,0.002664911,0.002513568,0.004054854,0.0004166662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002935965,"about_ca_system_score_gemma":0.004349188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01422266,"about_ca_topic_score_gemma":0.008908407,"domain_scores_codex":[0.9287676,0.06619183,0.001476531,0.002383657,0.0008532149,0.000327141],"domain_scores_gemma":[0.6074498,0.3752767,0.005943001,0.007177616,0.003552646,0.0006002985],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01025495,0.0002811359,0.011986,0.006511624,0.04665058,0.0004720358,0.0003275046,0.8751747,0.0005537902,0.01295386,0.002584437,0.03224937],"study_design_scores_gemma":[0.002861252,0.001240311,0.001849629,0.0009303359,0.01897573,0.000181198,0.00008990627,0.9454736,0.0004775977,0.0246227,0.003194226,0.0001036755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1852494,0.03599759,0.7540777,0.004855217,0.0009391882,0.004933209,0.005766483,0.001662899,0.006518347],"genre_scores_gemma":[0.789308,0.003368109,0.1968001,0.001237125,0.0001119522,0.004853813,0.00255691,0.0002558563,0.001508102],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8901735,"threshold_uncertainty_score":0.580825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9625775729860939,"score_gpt":0.6951755412614352,"score_spread":0.2674020317246587,"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."}}