{"id":"W2171533412","doi":"10.1109/icsmc.1997.635170","title":"Incorporating system dynamics in case-based reasoning for process operation support","year":2002,"lang":"en","type":"article","venue":"","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Case-based reasoning; Computer science; Process (computing); Adaptation (eye); Artificial intelligence; Search engine indexing; Reasoning system; Model-based reasoning; Machine learning; Knowledge representation and reasoning","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":[],"consensus_categories":[],"category_scores_codex":[0.0006775132,0.0001229716,0.0001450521,0.0001257911,0.0002294186,0.0002196803,0.0002660153,0.00007247294,0.00001087725],"category_scores_gemma":[0.00005600848,0.0001167301,0.00002995717,0.0003185014,0.00001040769,0.0004465919,0.00002774167,0.0001110329,0.00001143048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002032565,"about_ca_system_score_gemma":0.00008329004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001291342,"about_ca_topic_score_gemma":0.0002960173,"domain_scores_codex":[0.998924,0.00005118781,0.0003044166,0.0003273015,0.0001411129,0.0002519753],"domain_scores_gemma":[0.9993457,0.0001527177,0.0001173845,0.0002331709,0.00009167882,0.00005939298],"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":[0.00003746807,0.0002754122,0.1174048,0.002109181,0.0000319954,0.003078745,0.006189467,0.4196648,0.0001224102,0.3757314,0.002467523,0.07288677],"study_design_scores_gemma":[0.0003662416,0.00009656912,0.00001616444,0.0001371913,0.000002681287,0.0002475937,0.0003826859,0.9982495,0.0002511385,0.00006843973,0.00002045316,0.0001613641],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03263404,0.00001973383,0.9619166,0.0004187481,0.0001186474,0.0003315848,0.000005092814,0.0003030645,0.004252434],"genre_scores_gemma":[0.8352441,8.784577e-8,0.1643629,0.0001298445,0.00002645005,0.00006214865,0.00001952007,0.000009411685,0.0001455704],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.80261,"threshold_uncertainty_score":0.4760115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0210238429574389,"score_gpt":0.2476115395473319,"score_spread":0.226587696589893,"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."}}