{"id":"W1896391230","doi":"10.1109/cca.2015.7320696","title":"Small data-set EKF-based parameter estimation for a behavior-modification model","year":2015,"lang":"en","type":"article","venue":"","topic":"Cognitive Science and Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Extended Kalman filter; Observability; Estimator; Computer science; Kalman filter; Set (abstract data type); Monte Carlo method; Estimation theory; Cognitive dissonance; Artificial intelligence; Algorithm; Mathematics; Statistics; Applied mathematics; Psychology","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":[0.001404244,0.0006746234,0.0009105526,0.0003398049,0.0002939717,0.0006717636,0.0007994347,0.000947676,0.00112487],"category_scores_gemma":[0.009405795,0.0004563103,0.000544597,0.0002433525,0.0006391591,0.001040212,0.0006699855,0.001596867,0.0003272107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005719477,"about_ca_system_score_gemma":0.0007240053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00834621,"about_ca_topic_score_gemma":0.005539282,"domain_scores_codex":[0.9995605,0.0001476076,0.00003639838,0.0001355424,0.0000840414,0.00003589893],"domain_scores_gemma":[0.9961668,0.003007197,0.0002465357,0.0002865997,0.0002478162,0.00004508478],"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":[0.0001359136,0.0000683781,0.001892877,0.00009645093,0.00006684924,0.00009878971,0.0001317507,0.9545125,0.003170534,0.003792704,0.000264163,0.03576905],"study_design_scores_gemma":[0.000007662615,0.00001764089,0.0004730666,0.000005300888,0.00000485691,0.00001634908,0.000006185045,0.9978732,0.0004061936,0.001044398,0.0001372058,0.000007992326],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07236011,0.0001493235,0.9260346,0.0001516608,0.00003484176,0.00007528254,0.00007604874,0.0002825157,0.0008356785],"genre_scores_gemma":[0.8882253,0.0001260144,0.1097216,0.0000791546,0.00001944479,0.0002136677,0.0002158594,0.00003530515,0.001363661],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00834621,"threshold_uncertainty_score":0.01659524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5360898035727547,"score_gpt":0.3917075880258082,"score_spread":0.1443822155469465,"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."}}