{"id":"W2110358632","doi":"10.1109/robot.2001.932949","title":"Kinematic feasibility analysis of 3D grasps","year":2002,"lang":"en","type":"article","venue":"","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"GRASP; Kinematics; Object (grammar); Nonlinear system; Set (abstract data type); Computer science; Mathematical optimization; Optimization problem; Nonlinear programming; Mathematics; Artificial intelligence","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":[0.002139245,0.001031484,0.0008281419,0.001976978,0.0007882636,0.001495647,0.0009613814,0.001356905,0.004713618],"category_scores_gemma":[0.01021232,0.0009778212,0.00143221,0.001033951,0.002139153,0.001879386,0.002147763,0.0008320949,0.0006501098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008190844,"about_ca_system_score_gemma":0.001138696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001878113,"about_ca_topic_score_gemma":0.0008746139,"domain_scores_codex":[0.9983751,0.000464786,0.0001199847,0.0002394552,0.0006509526,0.0001498361],"domain_scores_gemma":[0.9951891,0.003189092,0.0007828991,0.0001878159,0.0005472709,0.0001038938],"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":[0.0001187209,0.00003185687,0.001102166,0.0002265019,0.00003132683,0.0003762651,0.000182475,0.8713019,0.00634399,0.09075026,0.0005915423,0.02894295],"study_design_scores_gemma":[0.00002169878,0.00006833924,0.0004580982,0.00005883283,0.00001248056,0.0001297499,0.00005530144,0.9319087,0.003284644,0.06242489,0.001545798,0.00003149671],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02303743,0.0001922381,0.972472,0.0001431006,0.000008759844,0.00005807769,0.0001080064,0.0001012372,0.00387907],"genre_scores_gemma":[0.6837225,0.0006988362,0.3111668,0.00006944232,0.00004215257,0.0004731882,0.0004788478,0.00009716005,0.003251023],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004713618,"threshold_uncertainty_score":0.01576865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05223858111536297,"score_gpt":0.2482839393627723,"score_spread":0.1960453582474093,"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."}}