{"id":"W3085000583","doi":"10.1016/j.compositesa.2020.106118","title":"Multi-scale analysis of the generated damage when machining pockets of 3D woven composite for repair applications using abrasive water jet process: Contamination analysis","year":2020,"lang":"en","type":"article","venue":"Composites Part A Applied Science and Manufacturing","topic":"Erosion and Abrasive Machining","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Safran Electronics (Canada)","funders":"","keywords":"Materials science; Machining; Composite number; Composite material; Abrasive; Jet (fluid); Water jet; Contamination; Mechanical engineering; Metallurgy; Engineering","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":[0.0001319029,0.0001809886,0.0001887663,0.0003976022,0.0002088516,0.000187363,0.0001861537,0.0003969907,0.00109062],"category_scores_gemma":[0.0001762828,0.000172116,0.0002347949,0.0002714611,0.0002405702,0.0002137,0.0001874668,0.0002873018,0.0001262517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001449761,"about_ca_system_score_gemma":0.00007296175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005586349,"about_ca_topic_score_gemma":0.001026019,"domain_scores_codex":[0.9998651,0.000006106647,0.000005143425,0.00002966699,0.00007312475,0.00002099684],"domain_scores_gemma":[0.9997429,0.0000643134,0.00006531023,0.00002502059,0.00008104931,0.00002141656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001227861,0.00003323442,0.002142159,0.00004229103,0.000007536232,0.00008490204,0.0000720344,0.001140533,0.9930696,0.00002772315,0.00003048427,0.003226741],"study_design_scores_gemma":[0.00001180036,0.000584574,0.1036054,0.000007570444,0.00004310362,0.0003144313,0.0002404314,0.02341056,0.8711424,0.00007604102,0.0005421179,0.00002156956],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951376,0.00008709144,0.004341287,0.0000054743,0.000003051053,0.000009476918,0.00006525449,0.00005072703,0.0003000676],"genre_scores_gemma":[0.9970595,0.00004375752,0.002391961,0.000006625344,0.000001322645,0.000009114185,0.00004878512,0.000009809495,0.0004291079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00109062,"threshold_uncertainty_score":0.00364846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0230012268938462,"score_gpt":0.2667439745683345,"score_spread":0.2437427476744883,"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."}}