{"id":"W2111338234","doi":"10.1109/have.2005.1545657","title":"Modelling haptic devices using a rule-based expert system","year":2005,"lang":"en","type":"article","venue":"","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Haptic technology; Computer science; Nonlinear system; Expert system; Controller (irrigation); Field (mathematics); Constant (computer programming); Set (abstract data type); Fuzzy logic; Control engineering; Control theory (sociology); Artificial intelligence; Machine learning; Control (management); Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008186323,0.0001196009,0.0001419157,0.00007398849,0.00006047884,0.00007902199,0.00007427948,0.00005592888,0.0001058967],"category_scores_gemma":[0.000001288589,0.0001073667,0.00004201868,0.00007480082,0.000006439095,0.0001336692,0.000004654964,0.0000471869,0.0001815646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001321527,"about_ca_system_score_gemma":0.00001613844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001161081,"about_ca_topic_score_gemma":0.00002846336,"domain_scores_codex":[0.9993362,0.00001249619,0.000235836,0.0001135775,0.0001273481,0.0001745518],"domain_scores_gemma":[0.9997181,0.00001951238,0.00001516495,0.0001502662,0.00002876925,0.00006823934],"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":[0.000001015566,0.000004760951,0.00002409723,0.00006186396,0.00001148605,0.000001314826,0.0001830925,0.9956115,0.002512309,0.0009778513,0.00007211182,0.0005385971],"study_design_scores_gemma":[0.0001962663,0.000003132189,0.000001915403,0.00008859568,0.000005692614,0.00001026509,0.0003681166,0.9923719,0.001771897,4.771475e-7,0.005036765,0.0001449516],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1533326,0.0006246211,0.8321304,0.0000376673,0.0002487048,0.0001201453,9.298862e-7,0.000903137,0.01260185],"genre_scores_gemma":[0.9627081,0.000002086428,0.03674176,0.0001052134,0.0002827157,0.00001156021,0.000001588464,0.00002891671,0.0001180457],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8093755,"threshold_uncertainty_score":0.4378287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03622674702536151,"score_gpt":0.2330926093847422,"score_spread":0.1968658623593807,"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."}}