{"id":"W2107180104","doi":"10.1109/tro.2009.2034831","title":"Autonomous Robotic Pick-and-Place of Microobjects","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Robotics","topic":"Advanced MEMS and NEMS Technologies","field":"Engineering","cited_by":190,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Microscale chemistry; SMT placement equipment; Microelectromechanical systems; Robot; Computer science; Mechanical engineering; Grippers; Nanotechnology; Simulation; Artificial intelligence; Engineering; Materials science","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":[0.0001998114,0.000304377,0.0004222997,0.0002201596,0.0003759164,0.0003895912,0.0005743678,0.0003780927,0.0008520567],"category_scores_gemma":[0.0003929244,0.0002994019,0.0001982802,0.000152708,0.0004815102,0.0004986778,0.0007009362,0.0002653687,0.0003545806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002058554,"about_ca_system_score_gemma":0.0003565807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005371742,"about_ca_topic_score_gemma":0.0009002018,"domain_scores_codex":[0.9997389,0.00002433061,0.00001394014,0.00006048866,0.0001290869,0.0000332658],"domain_scores_gemma":[0.9998291,0.00004217467,0.00004358151,0.00004385401,0.00001696524,0.00002438391],"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":[0.0001412595,0.00005974575,0.0006355079,0.0001083584,0.00002008275,0.0001811068,0.0001067314,0.009407518,0.8759549,0.002693746,0.0005837329,0.1101073],"study_design_scores_gemma":[0.00009345975,0.0005594856,0.003648723,0.00001192014,0.000032881,0.0006735991,0.00006329522,0.134368,0.839409,0.002430525,0.01865089,0.0000581746],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.510849,0.001630677,0.4797455,0.0002036641,0.0001359449,0.0001887239,0.00009429504,0.002253022,0.004899185],"genre_scores_gemma":[0.7470302,0.0006180503,0.2475958,0.00006568105,0.00003551692,0.0001134972,0.00009797729,0.00008379451,0.00435951],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008520567,"threshold_uncertainty_score":0.002850413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00902596309908651,"score_gpt":0.2150821012199766,"score_spread":0.2060561381208901,"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."}}