{"id":"W2968773736","doi":"10.1109/memea.2019.8802139","title":"In-Hand Telemanipulation Using a Robotic Hand and Biology-Inspired Haptic Sensing","year":2019,"lang":"en","type":"article","venue":"","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Ciência sem Fronteiras; Natural Sciences and Engineering Research Council of Canada; Ministério da Educação","keywords":"Teleoperation; Robotic hand; Haptic technology; Thumb; Grippers; Tactile sensor; Artificial intelligence; Computer science; Telerobotics; Computer vision; Robotics; Fuzzy logic; Robot; Object (grammar); Control engineering; Simulation; Engineering; Mobile robot","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001954271,0.0004043105,0.0004009492,0.0001545428,0.0003242914,0.0004014962,0.0005249077,0.0005084954,0.001146739],"category_scores_gemma":[0.0003464352,0.0001512763,0.0002119969,0.0001184272,0.0005344715,0.0006471829,0.0005134299,0.0003279874,0.00009761659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000276209,"about_ca_system_score_gemma":0.0002756161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006526725,"about_ca_topic_score_gemma":0.0006397467,"domain_scores_codex":[0.9999112,0.00001772271,0.000006376217,0.00002190413,0.00003030624,0.00001252282],"domain_scores_gemma":[0.9997844,0.00008579217,0.00006243651,0.00003093497,0.0000197123,0.00001670081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003142729,0.0002231841,0.000818219,0.0003942802,0.00007854328,0.0008321485,0.0002924558,0.1600271,0.637852,0.0109598,0.0007816051,0.1874265],"study_design_scores_gemma":[0.00006055614,0.000707623,0.001535582,0.00002241789,0.00004862798,0.0007546829,0.0000990362,0.8284815,0.1555361,0.00877142,0.003940375,0.00004203106],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1066324,0.0003727333,0.8888816,0.0002180327,0.00005819462,0.00004415634,0.00001289467,0.0003367701,0.003443236],"genre_scores_gemma":[0.8917648,0.0002441296,0.1055501,0.00007492343,0.0000318798,0.00004130832,0.00001212928,0.00002026508,0.002260473],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001146739,"threshold_uncertainty_score":0.003836215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03960136669063374,"score_gpt":0.2609953450999975,"score_spread":0.2213939784093638,"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."}}