{"id":"W2116954434","doi":"10.5194/ms-1-33-2010","title":"Grasp planning for a reconfigurable parallel robot with an underactuated arm structure","year":2010,"lang":"en","type":"article","venue":"Mechanical sciences","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"RWTH Aachen University; Deutsche Forschungsgemeinschaft","keywords":"GRASP; Underactuation; Object (grammar); Robotic arm; SMT placement equipment; Mechanism (biology); Computer science; Robot; Task (project management); Manipulator (device); Cartesian coordinate system; Control engineering; Engineering; Simulation; Artificial intelligence; Mathematics; Programming language","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002261495,0.0001049103,0.0001130815,0.00004817448,0.0002480376,0.0001368008,0.0001948741,0.00007613805,0.000429198],"category_scores_gemma":[0.00003710756,0.00007534808,0.00002094884,0.0001961377,0.00004048672,0.0002556631,0.000005619809,0.0002332739,0.000008692652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009149128,"about_ca_system_score_gemma":0.00001965844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002880073,"about_ca_topic_score_gemma":0.0002632296,"domain_scores_codex":[0.9992345,0.00001377651,0.0001206728,0.0002167377,0.0001538095,0.0002604952],"domain_scores_gemma":[0.9996636,0.00007475418,0.00002971067,0.0001039171,0.00002372838,0.0001042959],"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":[0.00001494908,0.00001003388,0.0001353811,0.000008107956,0.000007084084,0.000001225689,0.0001449297,0.9428988,0.04328338,0.0111187,0.00007300301,0.002304449],"study_design_scores_gemma":[0.0002661878,0.0002737248,0.0007693284,0.0000149715,0.000006903264,0.0000127905,0.000191838,0.986234,0.004012125,0.006417945,0.001599585,0.0002006159],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5659019,0.00002160137,0.4295543,0.0003219113,0.0006632946,0.0003203247,0.00000126806,0.0005056675,0.002709751],"genre_scores_gemma":[0.9657087,6.320678e-7,0.03405499,0.000072528,0.00007714399,0.000009550267,0.00001047985,0.00001259723,0.00005334948],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3998069,"threshold_uncertainty_score":0.4699417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04203087316142365,"score_gpt":0.2844718038539966,"score_spread":0.242440930692573,"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."}}