{"id":"W2289189593","doi":"10.1016/j.jclinepi.2016.02.016","title":"The rank-heat plot is a novel way to present the results from a network meta-analysis including multiple outcomes","year":2016,"lang":"en","type":"article","venue":"Journal of Clinical Epidemiology","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":228,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; St. Michael's Hospital","funders":"Canadian Institutes of Health Research","keywords":"Plot (graphics); Rank (graph theory); Meta-analysis; Statistics; Forest plot; Mathematics; Medicine; Combinatorics; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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","open_science","insufficient_payload"],"consensus_categories":["metaresearch","metaepi_broad","insufficient_payload"],"category_scores_codex":[0.7029265,0.0004639046,0.02496701,0.0002700604,0.0004761226,0.0002500689,0.005521808,0.0003138654,0.002379766],"category_scores_gemma":[0.8719454,0.0001019675,0.03225449,0.001644543,0.0003663217,0.000188484,0.0007340885,0.0007924315,0.000903766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004080846,"about_ca_system_score_gemma":0.0001110694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001588144,"about_ca_topic_score_gemma":0.0005128864,"domain_scores_codex":[0.702734,0.1828565,0.1041922,0.002202192,0.006764406,0.001250695],"domain_scores_gemma":[0.08775965,0.8696948,0.03329202,0.006233484,0.002305029,0.0007150697],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005180193,0.0001277624,0.3254817,0.000001930082,0.1771376,0.000005968709,0.0002780271,0.008254882,0.000009041832,0.001082963,0.4738538,0.01324831],"study_design_scores_gemma":[0.001228439,0.0001785014,0.3519685,0.00001657887,0.07277593,0.000008254709,0.0001415176,0.01126863,0.00000173019,0.0301516,0.5320674,0.0001929423],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.06671948,0.005264109,0.330687,0.5937325,0.002147872,0.0008230128,0.0001625174,0.000005264836,0.0004582249],"genre_scores_gemma":[0.9349288,0.0006789663,0.02788231,0.02623841,0.00235736,0.00003992466,0.000001647798,0.00002268394,0.007849942],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8682093,"threshold_uncertainty_score":0.9998742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.95740010273662,"score_gpt":0.669342945671616,"score_spread":0.288057157065004,"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."}}