{"id":"W4392002532","doi":"10.3389/fmtec.2024.1277152","title":"Anomaly detection in automated fibre placement: learning with data limitations","year":2024,"lang":"en","type":"article","venue":"Frontiers in Manufacturing Technology","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Anomaly detection; Anomaly (physics); Computer science; Artificial intelligence; Pattern recognition (psychology); Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002124552,0.0001571355,0.0001992554,0.001540922,0.00006485428,0.00006303078,0.0002079613,0.0003116617,0.000005198546],"category_scores_gemma":[0.00003621485,0.0001525312,0.00001655981,0.0007573515,0.00003169598,0.0002634794,0.00006716521,0.000691073,0.00001835321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002383217,"about_ca_system_score_gemma":0.00001188814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004747982,"about_ca_topic_score_gemma":0.000291563,"domain_scores_codex":[0.9989852,0.00003370327,0.0002660292,0.0003344472,0.0001032237,0.000277408],"domain_scores_gemma":[0.9995749,0.00003812959,0.0000252717,0.0003327748,0.000007747533,0.00002120386],"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":[0.0001086726,0.00003135757,0.008386934,0.0004612592,0.0001877264,0.0003341141,0.0004625634,0.5901223,0.003167222,0.00005735707,0.004921215,0.3917592],"study_design_scores_gemma":[0.000630867,0.000157963,0.002202263,0.0003991253,0.0000173597,0.00006282426,0.0009156187,0.9065251,0.04699683,0.0002207909,0.0415515,0.0003198035],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8883398,0.0007046444,0.1028402,0.00007387415,0.001752622,0.0003523772,0.000007058951,0.005283364,0.0006460649],"genre_scores_gemma":[0.9973473,0.00003647955,0.002386891,0.000001815502,0.000046692,0.00004599514,0.00002110165,0.00003982073,0.00007389688],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3914394,"threshold_uncertainty_score":0.6220043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01908094156064225,"score_gpt":0.2286261055192868,"score_spread":0.2095451639586446,"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."}}