{"id":"W4323657966","doi":"10.1016/j.jmrt.2023.03.006","title":"Experimental characterization of tool wear morphology in milling of Al520-MMC reinforced with SiC particles and additive elements Bi and Sn","year":2023,"lang":"en","type":"article","venue":"Journal of Materials Research and Technology","topic":"Aluminum Alloys Composites Properties","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Science and Technology, Israel; Natural Sciences and Engineering Research Council of Canada; École de technologie supérieure","keywords":"Materials science; Machinability; Abrasion (mechanical); Machining; Silicon carbide; Metallurgy; Tool wear; Tin; Composite material; Aluminium; Lubrication; Carbide","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004042273,0.0000688027,0.0002500127,0.0005649563,0.00002414892,0.00001526214,0.00007227395,0.00007639702,0.00001568294],"category_scores_gemma":[0.00005218226,0.00005457382,0.000005593993,0.0002490518,0.0002790373,0.0001272766,0.00009651489,0.0001071471,6.668394e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001704361,"about_ca_system_score_gemma":0.00001531178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007561494,"about_ca_topic_score_gemma":0.000001324781,"domain_scores_codex":[0.9992016,0.00004277268,0.0003568375,0.00007566774,0.0001352265,0.0001879048],"domain_scores_gemma":[0.9996687,0.00004512376,0.000095485,0.00006472346,0.00009938198,0.00002656145],"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":[0.0002241852,0.0000101836,0.001617903,0.00007372697,0.00003740765,0.0000320469,0.0003428302,0.00001723809,0.9968905,0.0001422512,0.000005654856,0.0006060431],"study_design_scores_gemma":[0.0006490071,0.001056121,0.003284829,0.0001297078,0.000003550944,0.00007318842,0.0007591554,0.0005114503,0.9933531,0.0001157208,0.00001587132,0.00004825335],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999504,0.0002127451,0.00001604615,0.00008011302,0.00002643809,0.0001258487,0.00001473499,0.00001619207,0.000003916143],"genre_scores_gemma":[0.9987289,0.0009032299,0.0003199556,0.00000151974,0.00001302722,0.00001013637,0.000004043875,0.00001137594,0.000007765972],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003537384,"threshold_uncertainty_score":0.2225456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02320972395188607,"score_gpt":0.2685392975383509,"score_spread":0.2453295735864648,"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."}}