{"id":"W2108257036","doi":"10.1109/icia.2007.4295780","title":"Automated Microassembly Task Execution Using Vision-Based Feedback Control","year":2007,"lang":"en","type":"article","venue":"","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"CMC Microsystems","keywords":"GRASP; Automation; Task (project management); Process (computing); Computer science; Grippers; SMT placement equipment; Microelectromechanical systems; Control engineering; Controller (irrigation); Position (finance); Fuzzy logic; Machine vision; Fuzzy control system; Control system; Robot; Artificial intelligence; Engineering; Mechanical engineering; Systems engineering; Electrical engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002037047,0.0005205058,0.0003201697,0.0003128898,0.0002498742,0.0003639402,0.0005845501,0.0003852226,0.001587171],"category_scores_gemma":[0.0006496951,0.0002036911,0.0001854976,0.0001148893,0.0002482627,0.0003426064,0.0002878231,0.0002948008,0.0003642975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000227707,"about_ca_system_score_gemma":0.0004727136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001654707,"about_ca_topic_score_gemma":0.001737145,"domain_scores_codex":[0.9997564,0.00001804387,0.00001084678,0.00005147334,0.0001333568,0.00002987678],"domain_scores_gemma":[0.9997603,0.00007304586,0.00005029608,0.00002224173,0.00006905319,0.00002508924],"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":[0.0003866176,0.0002102173,0.0004520004,0.0001402677,0.00002064192,0.0001901312,0.0001434547,0.03872598,0.6379145,0.001547672,0.001250834,0.3190177],"study_design_scores_gemma":[0.0001391319,0.0006531228,0.00394931,0.0000294984,0.00003355122,0.0003685628,0.00004931362,0.6646737,0.3213714,0.001795082,0.006871589,0.00006576783],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1189805,0.0005104994,0.8712853,0.0001318299,0.0001174627,0.0001652302,0.00004636097,0.00449347,0.004269344],"genre_scores_gemma":[0.7965388,0.0002443616,0.1991706,0.00009596662,0.0000311099,0.0001398797,0.00009099299,0.0001012199,0.003587033],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001654707,"threshold_uncertainty_score":0.005309641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008086313343876704,"score_gpt":0.2704109524880057,"score_spread":0.262324639144129,"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."}}