{"id":"W1975045544","doi":"10.1016/j.dss.2006.08.003","title":"Maintaining robust decision capabilities: An integrative human–systems approach","year":2006,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bishop's University; HEC Montréal","funders":"HEC Montréal; Universiteit Antwerpen; Memorial University of Newfoundland","keywords":"Multidisciplinary approach; Computer science; Risk analysis (engineering); Resource (disambiguation); Process management; Management science; Decision support system; Knowledge management; Artificial intelligence; Business; Engineering","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":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0202072,0.001228002,0.002826244,0.002590488,0.001651447,0.005639401,0.003925413,0.0007058292,0.001559637],"category_scores_gemma":[0.003652493,0.0008398509,0.0008626003,0.003047939,0.0003809708,0.002230561,0.0008567013,0.0007970434,0.001912255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006065338,"about_ca_system_score_gemma":0.0003735553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003673457,"about_ca_topic_score_gemma":0.0004706583,"domain_scores_codex":[0.9763975,0.00185835,0.007368215,0.003501663,0.009301897,0.001572429],"domain_scores_gemma":[0.9802579,0.008993106,0.002305981,0.004792062,0.00277856,0.0008724158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005575602,0.001052777,0.02057361,0.00005948226,0.00009996249,0.0004536384,0.00343575,0.2604747,0.0007334459,0.2950729,0.3941008,0.02338541],"study_design_scores_gemma":[0.003866036,0.001184258,0.008515864,0.0009927202,0.00007216695,0.001885652,0.09091528,0.3603682,0.00003079534,0.1074604,0.4219459,0.002762764],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.200445,0.001459662,0.7105039,0.00001678693,0.005992663,0.00198434,0.0001953445,0.0004447291,0.07895752],"genre_scores_gemma":[0.9659827,0.000003744434,0.01189675,0.00006408073,0.001958573,0.0002945153,0.0001065314,0.0001570933,0.01953598],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7655377,"threshold_uncertainty_score":0.9996483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1184158006361843,"score_gpt":0.3772495444537616,"score_spread":0.2588337438175773,"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."}}