{"id":"W4405024469","doi":"10.3390/ndt2040032","title":"Advanced Defect Detection on Curved Aeronautical Surfaces Through Infrared Imaging and Deep Learning","year":2024,"lang":"en","type":"article","venue":"NDT","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Rimouski; Université Laval","funders":"Agency for Science, Technology and Research","keywords":"Aerospace; Robustness (evolution); Deep learning; Computer science; Artificial intelligence; Segmentation; Computer vision; Machine learning; Reliability engineering; Engineering; Aerospace 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":[0.0001903241,0.0001383003,0.0001409265,0.00007998205,0.0001120222,0.0001363403,0.00002913597,0.00009787448,0.00003101543],"category_scores_gemma":[0.00007837639,0.000127135,0.00006366865,0.0002085507,0.00001664946,0.0002396869,0.0000139594,0.000376392,0.00008735716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008802444,"about_ca_system_score_gemma":0.000005229509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002198459,"about_ca_topic_score_gemma":0.00001292127,"domain_scores_codex":[0.9992352,0.00005674683,0.000170787,0.0002102851,0.0001373365,0.0001896885],"domain_scores_gemma":[0.9996845,0.0001522173,0.00001389796,0.00009022728,0.00001749986,0.00004172378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008252255,0.0000105255,0.000775319,0.0002253636,0.00008521282,0.00003815975,0.00100371,0.06205999,0.05428991,0.000326527,0.000220314,0.8808824],"study_design_scores_gemma":[0.001194464,0.0004433022,0.005838119,0.0005720218,0.00006956787,0.0001127302,0.0007666654,0.74322,0.07762259,0.0009444056,0.1684705,0.0007456624],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9572924,0.003524227,0.02776154,0.00001844163,0.002166651,0.000210253,0.000001769685,0.001245453,0.007779306],"genre_scores_gemma":[0.9993914,0.0000856417,0.0001218327,0.00001013791,0.0001922322,0.00001566647,0.000001925908,0.00003618775,0.0001449413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8801368,"threshold_uncertainty_score":0.5184417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01111624813963371,"score_gpt":0.240973621254154,"score_spread":0.2298573731145203,"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."}}