{"id":"W6958231004","doi":"10.6084/m9.figshare.12872405.v1","title":"Additional file 1 of LEVEL (Logical Explanations & Visualizations of Estimates in Linear mixed models): recommendations for reporting multilevel data and analyses","year":2020,"lang":"en","type":"article","venue":"Figshare","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Population Health Research Institute; McMaster University","funders":"","keywords":"Logistic regression; Logistic model tree; Regression diagnostic; Factor regression model; Regression analysis; Log-linear model; Proper linear model; Linear regression","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007480245,0.001346555,0.001661782,0.003671089,0.001069616,0.002782648,0.003117371,0.001544123,0.9142909],"category_scores_gemma":[0.1043875,0.001362197,0.001493124,0.005329379,0.0004527563,0.0028565,0.00199617,0.001732272,0.2819793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001486165,"about_ca_system_score_gemma":0.003566321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009521726,"about_ca_topic_score_gemma":0.01563019,"domain_scores_codex":[0.9975139,0.001126925,0.0003823622,0.000348963,0.0004385282,0.000189366],"domain_scores_gemma":[0.8853576,0.09943888,0.003062843,0.00430622,0.006696356,0.001138156],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001356454,0.00004784252,0.0009765152,0.001599832,0.00003748554,0.00002823204,0.0001203285,0.0003887902,0.00004150391,0.001436375,0.9836142,0.01157334],"study_design_scores_gemma":[0.002270764,0.0001404215,0.009541147,0.003747122,0.0001937885,0.0002643087,0.0005463411,0.00343149,0.0007445233,0.02810922,0.9508421,0.0001687005],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.0002449055,0.00004600931,0.005066651,0.0003419321,0.00008416653,0.0003156562,0.987792,0.002971809,0.00313688],"genre_scores_gemma":[0.01999644,0.0004735558,0.0873647,0.001893503,0.0004400432,0.01350974,0.8094179,0.02454617,0.04235797],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9925197,"threshold_uncertainty_score":0.1222535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8208900910738924,"score_gpt":0.5472691949162407,"score_spread":0.2736208961576517,"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."}}