{"id":"W2953535203","doi":"10.1016/j.jval.2019.04.1175","title":"PMU12 SCALABLE DECISION-ANALYTIC MODELLING WITH INFLUENCE DIAGRAMS","year":2019,"lang":"en","type":"article","venue":"Value in Health","topic":"Mental Health Research Topics","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Influence diagram; Computer science; Decision tree; Bayesian network; Graphical model; Decision engineering; Decision analysis; Machine learning; Scalability; Artificial intelligence; Evidential reasoning approach; Decision problem; Representation (politics); Data mining; Decision support system; Business decision mapping; Mathematics; Algorithm","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":[],"consensus_categories":[],"category_scores_codex":[0.003755084,0.00153883,0.001590856,0.001396437,0.00119738,0.003238137,0.002449091,0.001856143,0.02290972],"category_scores_gemma":[0.02893818,0.001618374,0.002980643,0.001252137,0.0006265601,0.002510212,0.003167495,0.002201898,0.003300464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001241947,"about_ca_system_score_gemma":0.003121943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01639195,"about_ca_topic_score_gemma":0.01429365,"domain_scores_codex":[0.9972011,0.001310553,0.000192505,0.0003837191,0.0007255659,0.0001865369],"domain_scores_gemma":[0.9870957,0.01032334,0.0002987774,0.001169234,0.000879693,0.0002331899],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004108011,0.0002105937,0.002700106,0.0005941047,0.0002866287,0.000188454,0.0004173391,0.754169,0.001279125,0.07001377,0.01239174,0.1573383],"study_design_scores_gemma":[0.00004127455,0.00001826607,0.00005777904,0.00002753703,0.00001921848,0.00001716975,0.00001418677,0.9705616,0.0005846763,0.02326692,0.005380624,0.00001083386],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007507834,0.0001230276,0.9776214,0.0002881838,0.00007077101,0.0002305539,0.001716136,0.007388401,0.005053584],"genre_scores_gemma":[0.2182251,0.0002340789,0.7719266,0.000168006,0.00006312736,0.001187273,0.003060583,0.001607394,0.003527883],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02290972,"threshold_uncertainty_score":0.07664067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09826136734443984,"score_gpt":0.4127631678258993,"score_spread":0.3145018004814594,"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."}}