{"id":"W2542542810","doi":"10.1109/iecon.1991.239158","title":"An innovative robotic gripper for grasping and handling research","year":2002,"lang":"en","type":"article","venue":"","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Actuator; Computer science; Grippers; Degrees of freedom (physics and chemistry); Robot end effector; Planar; Artificial intelligence; Robotics; Robotic arm; Variety (cybernetics); Robot; Control engineering; Engineering; Mechanical engineering; Computer graphics (images)","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":[0.0004784614,0.0006004571,0.0005512457,0.000708681,0.0004465735,0.0007646253,0.001169946,0.00114126,0.00350147],"category_scores_gemma":[0.0004949685,0.0003187073,0.0003837181,0.0006352682,0.0007249533,0.001398042,0.00108569,0.0006840035,0.002031252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002867362,"about_ca_system_score_gemma":0.0004634698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001138059,"about_ca_topic_score_gemma":0.0001622171,"domain_scores_codex":[0.9994739,0.00005748193,0.00002189779,0.0001267184,0.0002786624,0.00004136444],"domain_scores_gemma":[0.999763,0.00005703652,0.00002986627,0.0000551319,0.00005650604,0.00003848882],"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":[0.0001574859,0.000077892,0.0004531116,0.000721626,0.00003765415,0.0007171694,0.0001412682,0.003539826,0.5696175,0.04518269,0.009194632,0.3701591],"study_design_scores_gemma":[0.0001813079,0.001393449,0.002355043,0.0001673245,0.0001176027,0.007947396,0.00006975946,0.0521374,0.3030884,0.02731179,0.6050425,0.0001881244],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02671592,0.007033115,0.9262732,0.0006842515,0.0006601728,0.0002518217,0.0002155511,0.005733289,0.03243262],"genre_scores_gemma":[0.1067479,0.003338238,0.8599867,0.0009200016,0.0002169139,0.0003640884,0.0004461432,0.0001848296,0.02779507],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00350147,"threshold_uncertainty_score":0.01171362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1667466687253839,"score_gpt":0.3513716911136726,"score_spread":0.1846250223882887,"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."}}