{"id":"W4283262243","doi":"10.21203/rs.3.rs-1755435/v1","title":"Design and Analysis of a Welding Inspection Robot","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Science and Technology Commission of Shanghai Municipality; Natural Science Foundation of Shanghai","keywords":"Chassis; Robot; Welding; Process (computing); Task (project management); Robot welding; Computer science; Visual inspection; Engineering; Real-time computing; Simulation; Artificial intelligence; Mechanical engineering; Systems engineering","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":[0.001092242,0.00007635931,0.0001853823,0.001243813,0.000133932,0.00005329793,0.0001023297,0.00006609983,0.0004655657],"category_scores_gemma":[0.00008342676,0.00008708632,0.00006661202,0.001199142,0.00002777777,0.00004489524,0.0002209165,0.0007163026,0.000002275743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001294068,"about_ca_system_score_gemma":0.00002177116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007642684,"about_ca_topic_score_gemma":0.000006095552,"domain_scores_codex":[0.9988181,0.000283972,0.0001608648,0.0001791184,0.0003854169,0.0001725466],"domain_scores_gemma":[0.9994633,0.0001785619,0.0000247141,0.0002073982,0.00007455485,0.00005151311],"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":[0.000006910794,0.000007394443,0.009139625,0.0001617361,0.0002412094,0.000002795958,0.0007959365,0.9874883,0.0005471624,0.0003671028,0.00003476385,0.001207049],"study_design_scores_gemma":[0.00005454583,0.00002318133,0.09221046,0.00002983804,0.00004636604,3.781807e-7,0.0003927618,0.9068145,0.0001531397,0.0001015124,0.0001007638,0.00007253903],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2246183,0.001327008,0.7701037,0.00007161153,0.0001281654,0.0004307339,0.000001906672,0.0003490097,0.002969572],"genre_scores_gemma":[0.9972536,0.0001990789,0.002397961,0.00000120515,0.00002156639,0.00003956827,0.00002069164,0.00001715958,0.00004914511],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7726353,"threshold_uncertainty_score":0.5097618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1266946971238707,"score_gpt":0.3887508604335951,"score_spread":0.2620561633097244,"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."}}