{"id":"W2013059900","doi":"10.1108/01439910510573273","title":"Optimum grasp planner and vision‐guided grasping using a three‐finger hand","year":2005,"lang":"en","type":"article","venue":"Industrial Robot the international journal of robotics research and application","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"GRASP; Revolute joint; Artificial intelligence; Computer vision; Computer science; SMT placement equipment; Object (grammar); Machine vision; Robot; Robotic hand; Robotics; Grippers; Robotic arm; Human–computer interaction; Control engineering; 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":[0.0003318093,0.0003882731,0.0004634468,0.0004579888,0.0002306017,0.0004805942,0.0005394223,0.0005437122,0.001898204],"category_scores_gemma":[0.0005036478,0.0003507183,0.0005579484,0.0002879987,0.0005339551,0.0004773572,0.0004378112,0.0003475957,0.0002329401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005350966,"about_ca_system_score_gemma":0.0009368767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002924405,"about_ca_topic_score_gemma":0.002222845,"domain_scores_codex":[0.9998167,0.00003039832,0.00001235685,0.00005503805,0.00006137485,0.00002414849],"domain_scores_gemma":[0.9998313,0.00007476101,0.00003581918,0.00002015165,0.00002149072,0.00001642999],"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":[0.0001588992,0.00004405395,0.0003385818,0.0001565593,0.00003196934,0.0002120602,0.00009985167,0.848048,0.05137245,0.009638388,0.0004745664,0.08942466],"study_design_scores_gemma":[0.00001706628,0.00006810138,0.0001780767,0.000007821354,0.00000604044,0.00005329625,0.00001271909,0.9922755,0.004281151,0.002383113,0.0007060394,0.00001104439],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02078706,0.0001607931,0.9769073,0.00004053431,0.00001075695,0.0000396763,0.00002175639,0.0003474787,0.001684667],"genre_scores_gemma":[0.6809543,0.0001327083,0.316199,0.00003295015,0.000008057628,0.00009161545,0.00004352449,0.00004627823,0.002491635],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002924405,"threshold_uncertainty_score":0.0063501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1566905864763294,"score_gpt":0.3962675947619855,"score_spread":0.2395770082856561,"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."}}