{"id":"W4289262412","doi":"10.3758/s13428-022-01892-7","title":"Multilevel multivariate meta-analysis made easy: An introduction to MLMVmeta","year":2022,"lang":"en","type":"review","venue":"Behavior Research Methods","topic":"Behavioral Health and Interventions","field":"Psychology","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Multivariate statistics; Computer science; Multilevel model; Multivariate analysis; Meta-analysis; Data mining; Machine learning; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.07400829,0.003838962,0.009205838,0.007536141,0.0008060045,0.005963191,0.004846626,0.002725072,0.03764605],"category_scores_gemma":[0.2322229,0.003920687,0.02738313,0.008034727,0.001198558,0.004095887,0.006089785,0.009733346,0.006502181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001755784,"about_ca_system_score_gemma":0.007188555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003623785,"about_ca_topic_score_gemma":0.007673187,"domain_scores_codex":[0.9190318,0.06325816,0.009175079,0.002693648,0.005514087,0.0003272396],"domain_scores_gemma":[0.8191153,0.1597682,0.004699115,0.01035017,0.005275277,0.0007919332],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001623941,0.0001801702,0.001619655,0.1182564,0.07398954,0.0003072378,0.0006909307,0.005194476,0.001942825,0.04375429,0.1590836,0.5933569],"study_design_scores_gemma":[0.004299006,0.0008704981,0.006067227,0.05832689,0.07077777,0.001085545,0.0002476171,0.03513541,0.002691267,0.2820502,0.5372959,0.001152656],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001060017,0.2608622,0.6868963,0.01145926,0.009497083,0.003701811,0.01375186,0.01052177,0.002249761],"genre_scores_gemma":[0.008871687,0.0503724,0.9112613,0.004145409,0.002677438,0.01582817,0.00211773,0.002728443,0.001997345],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9259917,"threshold_uncertainty_score":0.391398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9002596806621552,"score_gpt":0.757045118444534,"score_spread":0.1432145622176212,"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."}}