{"id":"W1908932824","doi":"10.6082/m16t0jsw","title":"Gearing Up: Visualizing Decision Support for Manufacturing","year":2010,"lang":"en","type":"article","venue":"Knowledge@UChicago (University of Chicago)","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Decision support system; Variety (cybernetics); Work (physics); Domain (mathematical analysis); Order (exchange); Modal; Computer science; Management science; Engineering; Operations research; Business; Artificial intelligence; Mathematics","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":[0.0008607043,0.001233019,0.0005347711,0.002552242,0.0006023696,0.003206937,0.001092294,0.001168911,0.0214409],"category_scores_gemma":[0.004715681,0.0003328336,0.001116386,0.001949228,0.0004689651,0.00249345,0.00224454,0.001007049,0.002905179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004733536,"about_ca_system_score_gemma":0.0006614979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003746448,"about_ca_topic_score_gemma":0.003583262,"domain_scores_codex":[0.9995742,0.0001772243,0.00003476612,0.00006490014,0.0001101934,0.00003856903],"domain_scores_gemma":[0.9989457,0.0005414626,0.00006549158,0.0001666054,0.0001776289,0.0001030788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007270738,0.0002556081,0.005459204,0.002111995,0.0003044684,0.001600631,0.005059794,0.06077957,0.0200535,0.1026169,0.1411695,0.6598618],"study_design_scores_gemma":[0.0001953665,0.0001937917,0.005083682,0.000925321,0.0001650032,0.0007905395,0.001587363,0.3583668,0.01733836,0.222515,0.3926504,0.0001883494],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03042203,0.004144915,0.8801325,0.003752929,0.0007032237,0.0004492133,0.009482016,0.04306256,0.02785057],"genre_scores_gemma":[0.2597716,0.002140446,0.7184001,0.0004891331,0.0001545218,0.0004105699,0.006611524,0.002780697,0.009241397],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0214409,"threshold_uncertainty_score":0.07172692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01364225345861649,"score_gpt":0.2319531531562558,"score_spread":0.2183108996976393,"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."}}