{"id":"W4367724231","doi":"10.1007/978-3-031-23615-0_16","title":"Sensitivity and Uncertainty Analysis of SLM Process Using Artificial Neural Network","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in mechanical engineering","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Sensitivity (control systems); Artificial neural network; Computer science; Process (computing); Artificial intelligence; Biological system; Engineering; Electronic engineering; Biology","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":[0.001926836,0.0007364022,0.00100785,0.000815157,0.000513597,0.001234144,0.000711271,0.000983187,0.001326222],"category_scores_gemma":[0.004298147,0.00058927,0.001125345,0.0006509338,0.0008315959,0.001368374,0.001102473,0.0009433989,0.00007901663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001567195,"about_ca_system_score_gemma":0.0006847402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008303711,"about_ca_topic_score_gemma":0.00347275,"domain_scores_codex":[0.9992662,0.0002878381,0.00003101181,0.0001253567,0.0002195018,0.00007012929],"domain_scores_gemma":[0.9974751,0.002019461,0.0001616977,0.00007677385,0.0002429503,0.0000240281],"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":[0.00004577225,0.00001170279,0.0002124064,0.00003608211,0.00002041334,0.00003161834,0.00001387651,0.9931412,0.001302863,0.001686738,0.0000710481,0.003426311],"study_design_scores_gemma":[6.544128e-7,0.000005915994,0.00008878389,0.000001296201,0.000002115047,0.000002510866,0.000001611432,0.9990652,0.0002974962,0.0005110763,0.00002094943,0.000002413451],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1801932,0.001209993,0.8066508,0.0004551401,0.00009645471,0.00009618566,0.0001940902,0.0003474929,0.01075666],"genre_scores_gemma":[0.9906932,0.0001743512,0.007661811,0.00002426297,0.00001416411,0.00003261281,0.00004636125,0.00002701766,0.00132629],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008303711,"threshold_uncertainty_score":0.01651073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01583897203900608,"score_gpt":0.2252600648313834,"score_spread":0.2094210927923773,"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."}}