{"id":"W4392974616","doi":"10.1016/j.procs.2024.02.035","title":"Defect detection in additive manufacturing using image processing techniques","year":2024,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue","funders":"Ministère des relations internationales et de la Francophonie","keywords":"Computer science; Image processing; Computer vision; Artificial intelligence; Image (mathematics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003476072,0.0004614213,0.0002865597,0.001633,0.0001505414,0.0006952036,0.0005631762,0.0005812809,0.001147985],"category_scores_gemma":[0.0008455427,0.0002718292,0.0004565624,0.0008156924,0.0003326671,0.0005367026,0.0003492025,0.0003688287,0.0005193125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003066992,"about_ca_system_score_gemma":0.0002502622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000673722,"about_ca_topic_score_gemma":0.0006222515,"domain_scores_codex":[0.9994248,0.00007185978,0.00002295984,0.00008364979,0.0003675516,0.00002910867],"domain_scores_gemma":[0.9995021,0.0001905307,0.00006959113,0.00007405401,0.0001535503,0.00001013268],"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":[0.0001583633,0.00008316758,0.002419581,0.0004494616,0.00005675421,0.000193559,0.0002938887,0.01788361,0.3466477,0.003695216,0.001408727,0.62671],"study_design_scores_gemma":[0.00002400997,0.0003404384,0.01039275,0.00008406888,0.00008256983,0.001190782,0.0001302477,0.4773741,0.4963685,0.002661244,0.01127955,0.00007180732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06486294,0.0009320833,0.9295691,0.00006513078,0.00004253118,0.00005832614,0.00008732457,0.0016964,0.002686189],"genre_scores_gemma":[0.4125697,0.0008693766,0.5833429,0.00004621606,0.00002888621,0.00007036309,0.0001777412,0.0001251224,0.002769741],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001633,"threshold_uncertainty_score":0.003840387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01436283497835114,"score_gpt":0.2544084405960031,"score_spread":0.240045605617652,"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."}}