{"id":"W2057939818","doi":"10.1109/rose.2014.6952985","title":"Instrumented compliant wrist for dexterous robotic interaction","year":2014,"lang":"en","type":"article","venue":"","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Robotics; Context (archaeology); Artificial intelligence; Computer science; Human–computer interaction; Robot; Focus (optics); Feature (linguistics); Mobile robot; Simulation; Computer vision; Engineering; Systems engineering","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":[0.0005366645,0.0006775367,0.0005262902,0.0003887784,0.0002948084,0.0007010094,0.001312674,0.000936376,0.002511382],"category_scores_gemma":[0.0009129125,0.0003488598,0.0004001929,0.0002519538,0.0005556023,0.0004710123,0.0007391614,0.0005284343,0.001279939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001514013,"about_ca_system_score_gemma":0.0003837168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009860472,"about_ca_topic_score_gemma":0.0001689252,"domain_scores_codex":[0.9992691,0.00008250909,0.00007237813,0.0001318497,0.0003946912,0.00004949608],"domain_scores_gemma":[0.9992995,0.000132211,0.0001802991,0.0002205196,0.00009672028,0.0000706535],"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":[0.0001516262,0.00008428132,0.0004020699,0.0003677015,0.00002096286,0.0005695819,0.0001614992,0.002369211,0.9297093,0.00194731,0.0005851421,0.06363129],"study_design_scores_gemma":[0.0001686755,0.005398148,0.00785081,0.0001492547,0.0001322997,0.006077482,0.0001264444,0.02948449,0.8897764,0.001238436,0.05941059,0.0001871105],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1252747,0.001247193,0.8619971,0.000126806,0.0002844751,0.0003409307,0.0001085187,0.002562898,0.008057355],"genre_scores_gemma":[0.4867164,0.0005455877,0.502363,0.0001901353,0.00007468869,0.0003432942,0.0001661456,0.0001416322,0.009459157],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002511382,"threshold_uncertainty_score":0.008401394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02680517358050322,"score_gpt":0.2490565554752799,"score_spread":0.2222513818947767,"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."}}