{"id":"W2109073894","doi":"10.1109/robot.2002.1013616","title":"Automated inspection system using range data","year":2003,"lang":"en","type":"article","venue":"","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Point cloud; Computer science; Range (aeronautics); Process (computing); Noise (video); Set (abstract data type); Artificial intelligence; Dispersion (optics); Computer vision; Automated X-ray inspection; CAD; Engineering drawing; Engineering; Image processing; Optics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000294422,0.00008564237,0.0001171782,0.00008663838,0.00008465606,0.0000463245,0.00006960503,0.0001041986,0.00001636868],"category_scores_gemma":[0.00002353757,0.00007673163,0.00002010132,0.0002586905,0.000004619137,0.0002003984,0.00001203796,0.00007701883,0.0001049269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000131174,"about_ca_system_score_gemma":0.00001070669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001475343,"about_ca_topic_score_gemma":0.00001210577,"domain_scores_codex":[0.9993891,0.00004499715,0.0001930416,0.0001359823,0.0001089271,0.0001279945],"domain_scores_gemma":[0.9995438,0.00001270899,0.00002086845,0.0003608179,0.00002391841,0.00003787542],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009227108,0.0001456006,0.004792755,0.001822525,0.0007762271,0.0001486332,0.0007725014,0.334858,0.2243489,0.02345844,0.3983654,0.01041877],"study_design_scores_gemma":[0.0002886314,0.000008964616,0.00007447258,0.00003512229,0.00001079937,0.00008810678,0.000221162,0.9858249,0.003711407,7.801995e-7,0.009625942,0.0001097312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6699901,0.0002948748,0.1480888,0.000002922696,0.008500336,0.0006013599,0.00002621408,0.04568737,0.126808],"genre_scores_gemma":[0.9992277,0.000001433965,0.000560861,0.000002635471,0.000141913,0.000002474898,0.000005078185,0.00002093977,0.00003696074],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6509669,"threshold_uncertainty_score":0.3129025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07293630210380629,"score_gpt":0.2725051493526376,"score_spread":0.1995688472488313,"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."}}