{"id":"W4388661171","doi":"10.3390/ma16227157","title":"Experimental Investigation on Machinability of α/β Titanium Alloys with Different Microstructures","year":2023,"lang":"en","type":"article","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; National Research Council Canada","funders":"Natural Sciences and Engineering Research Council of Canada; Academy of Scientific Research and Technology","keywords":"Machinability; Materials science; Microstructure; Martensite; Metallurgy; Martensitic stainless steel; Machining; Surface roughness; Surface finish; Tool wear; Titanium alloy; Layer (electronics); Titanium; Phase (matter); Deformation (meteorology); Composite material","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003739337,0.00008804965,0.0001144578,0.00003435834,0.00002448177,0.00001714193,0.00004459094,0.00002850335,0.00006069577],"category_scores_gemma":[0.000007581767,0.0000665105,0.000009208453,0.00006456966,0.00002425322,0.0000475164,0.00001347473,0.00002292128,0.000004848676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002449898,"about_ca_system_score_gemma":0.000003176156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000641287,"about_ca_topic_score_gemma":0.000001382891,"domain_scores_codex":[0.9996157,0.00001182774,0.0001207865,0.00009122514,0.00007220633,0.00008830491],"domain_scores_gemma":[0.9998318,0.00001225104,0.00002937477,0.00009427933,0.00001218445,0.00002010654],"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":[0.00003667975,0.000006273617,0.0003214458,0.0001186938,0.000007819978,5.887218e-7,0.0002412253,0.05756912,0.9411981,0.0003394008,0.00006115564,0.00009948837],"study_design_scores_gemma":[0.0001537287,0.00006884512,0.007980028,0.00002536602,0.000003487439,6.870008e-7,0.00004315317,0.0006574891,0.9906282,0.0003251188,0.00003856183,0.00007527971],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986067,0.00001540889,0.0006876613,0.00001347295,0.000217462,0.0001033174,0.00002918888,0.0002078684,0.0001189543],"genre_scores_gemma":[0.9990262,0.000006453603,0.0007968796,0.0000124605,0.00002859835,0.00001614344,0.00007305527,0.00002045034,0.00001974297],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05691163,"threshold_uncertainty_score":0.2712219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01127728698159387,"score_gpt":0.228044799310248,"score_spread":0.2167675123286542,"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."}}