{"id":"W4403901637","doi":"10.1016/j.mlwa.2024.100600","title":"Review of machine learning applications for defect detection in composite materials","year":2024,"lang":"en","type":"article","venue":"Machine Learning with Applications","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Composite number; Computer science; Materials science; Artificial intelligence; Machine learning; Composite material","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001282327,0.0008715093,0.0009797282,0.002343853,0.0002411721,0.0009338208,0.001067901,0.000994404,0.002917334],"category_scores_gemma":[0.002423316,0.0005316358,0.0007950606,0.002926977,0.0003882556,0.001408484,0.0004993177,0.001278518,0.002145399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005550224,"about_ca_system_score_gemma":0.0008434115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001095166,"about_ca_topic_score_gemma":0.001283711,"domain_scores_codex":[0.9994254,0.00009781486,0.0000727236,0.0001335155,0.0002419847,0.00002868146],"domain_scores_gemma":[0.9979482,0.001260722,0.000108265,0.00008162916,0.0005593085,0.00004195854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005736597,0.00006927938,0.0004196774,0.01179462,0.0001271132,0.00009656484,0.0000474664,0.003256693,0.003655934,0.006708179,0.02652849,0.9472386],"study_design_scores_gemma":[0.00001368945,0.0002179953,0.002337008,0.00425688,0.0002137128,0.0008183478,0.00005227183,0.006955462,0.006308953,0.006739134,0.9720045,0.00008208783],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000763933,0.9810396,0.01332953,0.0006571191,0.0005325409,0.00002414397,0.00008929791,0.0001047357,0.003459143],"genre_scores_gemma":[0.006581715,0.9756737,0.01363113,0.0005307385,0.0008639797,0.00003688699,0.0002202714,0.00004503664,0.002416605],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002917334,"threshold_uncertainty_score":0.009759426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01048036639401351,"score_gpt":0.2567022874481734,"score_spread":0.2462219210541599,"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."}}