{"id":"W2154853413","doi":"10.1017/s0263574701003988","title":"Robotic laser welding: seam sensor and laser focal frame registration","year":2002,"lang":"en","type":"article","venue":"Robotica","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Frame (networking); Computer vision; Robot; Computer science; Artificial intelligence; Calibration; Laser; Welding; Point (geometry); Robot welding; Engineering; Optics; Mechanical engineering; Mathematics; Physics","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":[0.00007870533,0.0001450112,0.0001514715,0.00006624156,0.00009290041,0.00008812494,0.00005591534,0.00009848631,0.0006230321],"category_scores_gemma":[0.00006731347,0.0001514706,0.00003718369,0.0001262432,0.00003039185,0.0001538727,0.0000142847,0.0002592157,0.0002706866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003085908,"about_ca_system_score_gemma":0.000002756129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005546672,"about_ca_topic_score_gemma":0.000009205792,"domain_scores_codex":[0.9992095,0.00003219574,0.0001901855,0.0001822004,0.0001483869,0.0002375664],"domain_scores_gemma":[0.9995878,0.00007041537,0.0000254509,0.000177805,0.00002299437,0.0001155107],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001762647,0.00001302567,0.00093403,0.00003313239,0.00001552274,0.0000101949,0.0001384651,0.9945302,0.0002237469,0.0005087446,0.003030558,0.0005606223],"study_design_scores_gemma":[0.0002472417,0.00002509929,0.005521825,0.00002859748,0.00002250168,0.00002316517,0.00004807287,0.9905018,0.0003484006,0.00007157162,0.002950041,0.0002116746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1637721,0.001129544,0.7427166,0.006636826,0.001548475,0.0007581573,0.000001503448,0.002664106,0.08077274],"genre_scores_gemma":[0.9924259,0.0000377336,0.004561471,0.0001295155,0.0001536944,0.00000448331,0.000005981898,0.00003696137,0.002644329],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8286538,"threshold_uncertainty_score":0.6821765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02572664161696125,"score_gpt":0.2150794282143215,"score_spread":0.1893527865973602,"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."}}