{"id":"W3161130397","doi":"10.1109/mim.2021.9436097","title":"A Modern Solution for an Old Calibration Problem","year":2021,"lang":"en","type":"article","venue":"IEEE Instrumentation & Measurement Magazine","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer vision; Artificial intelligence; Visual servoing; Robot calibration; Coordinate system; Robot end effector; Robot; Camera auto-calibration; Cartesian coordinate robot; Transformation matrix; Computer science; Robot kinematics; Frame (networking); Transformation (genetics); Camera resectioning; Kinematics; Mobile robot","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":[0.0002518423,0.000170581,0.0001450301,0.0000858105,0.0001109631,0.0001190317,0.00006171277,0.00007948106,0.00003210274],"category_scores_gemma":[0.00001859709,0.0001963581,0.00005647814,0.0001939844,0.00001354174,0.0004959881,0.000004947061,0.00006676558,0.00001519896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002647931,"about_ca_system_score_gemma":0.00006272912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007869705,"about_ca_topic_score_gemma":0.0002356804,"domain_scores_codex":[0.9986241,0.00004815399,0.0003781265,0.00025323,0.000464942,0.0002314036],"domain_scores_gemma":[0.9992679,0.000009233209,0.00006146347,0.0001965503,0.0003757149,0.00008909358],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000224532,0.00008701818,0.0002073538,0.0001256711,0.00003407132,0.000001056784,0.0002255675,0.4113863,0.5625908,0.000614749,0.002129844,0.02257511],"study_design_scores_gemma":[0.001077013,0.00009077603,0.0003723544,0.00003999141,0.00004235398,0.000003833032,0.00002690724,0.8701605,0.1257184,0.001118821,0.001141841,0.0002072443],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0470712,0.00007079975,0.95031,0.0002923677,0.0006510583,0.0005710865,0.00002296602,0.0002783532,0.000732179],"genre_scores_gemma":[0.9782462,0.00003144336,0.02051236,0.0001927375,0.0001801123,0.0001255758,0.0005100766,0.00005223087,0.0001492616],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.931175,"threshold_uncertainty_score":0.8007249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05026403560852995,"score_gpt":0.2481568963169223,"score_spread":0.1978928607083923,"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."}}