{"id":"W2746219630","doi":"10.1177/1729881417727326","title":"Active stability observer using artificial neural network for intuitive physical human–robot interaction","year":2017,"lang":"en","type":"article","venue":"International Journal of Advanced Robotic Systems","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Université du Québec à Chicoutimi","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Computer science; Artificial neural network; Robot; Observer (physics); Vibration; Control theory (sociology); Perceptron; Controller (irrigation); Stability (learning theory); Artificial intelligence; Obstacle; Transparency (behavior); Control engineering; Simulation; Machine learning; Control (management)","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":[0.0002792734,0.0001859306,0.0004173116,0.00008673791,0.0002378256,0.0003337218,0.0004431779,0.00006632644,0.00001113911],"category_scores_gemma":[0.0001966538,0.0001706529,0.0002146987,0.00003447385,0.00005688338,0.001016274,0.00003854822,0.000230597,0.000003877298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004533639,"about_ca_system_score_gemma":0.00003749583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000371458,"about_ca_topic_score_gemma":0.00003138801,"domain_scores_codex":[0.9984704,0.00006027466,0.0007010428,0.0001584537,0.0003956692,0.0002141092],"domain_scores_gemma":[0.9980546,0.0001746614,0.000650427,0.0002145607,0.0008152928,0.00009050443],"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":[0.0001403222,0.00005424668,0.0004361204,0.00003077868,0.0002615261,0.00001136611,0.000429363,0.9683644,0.02487406,0.002318291,0.00004233293,0.003037178],"study_design_scores_gemma":[0.001377901,0.0002151165,0.005969132,0.0005513311,0.00007814648,0.0002206701,0.002089679,0.9821503,0.00570538,0.0008934677,0.0004219986,0.0003269383],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8246707,0.00008226801,0.1557487,0.00009211679,0.01866774,0.0004029418,0.00002089438,0.00004510797,0.0002695733],"genre_scores_gemma":[0.9938607,0.000004080312,0.001457477,0.00001109516,0.004591563,0.00001587257,0.00000798212,0.00003209803,0.0000191973],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1691899,"threshold_uncertainty_score":0.6959025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08478082714686926,"score_gpt":0.349939356877321,"score_spread":0.2651585297304518,"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."}}