{"id":"W4210778605","doi":"10.1007/978-3-030-92529-1_110","title":"Machine Vision Sensor Based on Image Texture Analysis Applied to Industrial Anode Paste","year":2022,"lang":"en","type":"book-chapter","venue":"˜The œminerals, metals & materials series","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Alcoa (Canada)","funders":"","keywords":"Robustness (evolution); Anode; Artificial intelligence; Texture (cosmology); Process engineering; Materials science; Process (computing); Computer science; Computer vision; Pattern recognition (psychology); Engineering; Image (mathematics)","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001483385,0.001166038,0.002155233,0.00105412,0.0004431287,0.000600468,0.0005021683,0.000882327,0.009244687],"category_scores_gemma":[0.00003965226,0.0008804627,0.0006155799,0.0005214611,0.00008123925,0.0002087319,0.0002146515,0.0008332623,0.0004424624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000245621,"about_ca_system_score_gemma":0.00005457628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002800629,"about_ca_topic_score_gemma":0.00009170358,"domain_scores_codex":[0.995693,0.000307844,0.001458013,0.000885745,0.001059608,0.0005958245],"domain_scores_gemma":[0.9976119,0.0001808296,0.0005124243,0.001375637,0.0001145563,0.0002046951],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003055775,0.00006918539,0.000001698533,0.0003044509,0.003116052,0.0001378056,0.0002651784,0.1396081,0.807525,0.003804156,0.03796944,0.004143125],"study_design_scores_gemma":[0.001235454,0.000633556,0.00001040927,0.000137454,0.001898141,0.00002922598,0.00006906547,0.0008162248,0.02741177,0.0002234051,0.9660618,0.001473512],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06440794,0.001779536,0.006309265,0.00206926,0.04380834,0.01863818,0.02891673,0.006209829,0.8278609],"genre_scores_gemma":[0.6848928,0.0001089089,0.0004831201,0.0009003738,0.006633976,0.0007944943,0.002882729,0.0009051394,0.3023985],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9280924,"threshold_uncertainty_score":0.9993646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01732938421216915,"score_gpt":0.2216901910201135,"score_spread":0.2043608068079444,"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."}}