{"id":"W2963945072","doi":"10.1109/lra.2019.2931221","title":"Haptic Interface for Handshake Emulation","year":2019,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Handshake; Haptic technology; Trajectory; Interface (matter); Impedance control; Simulation; Hexapod; Computer science; Stiffness; Emulation; Robot; Control theory (sociology); Engineering; Control (management); Artificial intelligence; Asynchronous communication; Physics","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":[0.00007283201,0.00008051012,0.00009291407,0.00005708188,0.00007699068,0.0000900485,0.00005186573,0.00002972059,0.0000119066],"category_scores_gemma":[0.00004695628,0.00007509373,0.00003214915,0.0000580636,0.00001789326,0.0002157436,0.000006578955,0.00003959266,0.0000454355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001619958,"about_ca_system_score_gemma":0.000006098996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001972358,"about_ca_topic_score_gemma":9.28472e-7,"domain_scores_codex":[0.9993966,0.00002354944,0.0001515332,0.0001954354,0.0001108266,0.0001221123],"domain_scores_gemma":[0.9996341,0.0001393361,0.00008671519,0.0000896599,0.00001910437,0.00003111929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001028637,0.000008422874,0.00005269815,0.0000261044,0.00000219239,2.503185e-7,0.0001219907,0.1266128,0.8692753,0.001987196,0.00008703176,0.001815798],"study_design_scores_gemma":[0.0007013415,0.00004910347,0.002140482,0.00002421718,0.000009682403,0.000002689902,0.000009738916,0.9790171,0.01700673,0.0002918541,0.0006351211,0.0001118945],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5846262,0.000005857042,0.4115645,0.002918119,0.0004408093,0.0003297828,0.000004133867,0.00006148203,0.00004914663],"genre_scores_gemma":[0.9961702,0.000003037334,0.001868561,0.001643351,0.0000624743,0.00001286457,0.00000360918,0.00001064772,0.0002253134],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8524044,"threshold_uncertainty_score":0.3062234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0233205542543973,"score_gpt":0.255150766532253,"score_spread":0.2318302122778557,"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."}}