{"id":"W4315647912","doi":"10.3390/ma16020688","title":"Influence of Microstructure and Alloy Composition on the Machinability of α/β Titanium Alloys","year":2023,"lang":"en","type":"article","venue":"Materials","topic":"Advanced Machining and Optimization Techniques","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; National Research Council Canada","funders":"Natural Sciences and Engineering Research Council of Canada; Central Metallurgical Research and Development Institute; Academy of Scientific Research and Technology","keywords":"Machinability; Microstructure; Titanium alloy; Materials science; Machining; Titanium; Surface roughness; Composite material; Surface finish; Electrical discharge machining; Layer (electronics); Alloy; Metallurgy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003730084,0.0002400526,0.0002356568,0.0003353863,0.0002169228,0.0004669213,0.0002827031,0.0003130217,0.0005823947],"category_scores_gemma":[0.0008157487,0.0003457382,0.0002174086,0.0002022628,0.0002300246,0.0001975324,0.00015194,0.0002138513,0.0001739155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000266246,"about_ca_system_score_gemma":0.0001607914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001169937,"about_ca_topic_score_gemma":0.002369921,"domain_scores_codex":[0.9996394,0.00003710893,0.00003224581,0.00006484906,0.000169182,0.00005712397],"domain_scores_gemma":[0.9995546,0.00006842081,0.0001248712,0.00003734438,0.0001791331,0.00003567857],"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":[0.0001866428,0.0000138034,0.001798729,0.00006691612,0.00001376817,0.0000707805,0.00005149661,0.0004080199,0.994972,0.00002873762,0.00001412449,0.002375016],"study_design_scores_gemma":[0.00002718386,0.001397528,0.06839894,0.00001515563,0.00008840028,0.0003373445,0.00018872,0.002513389,0.9253861,0.0000441683,0.001586662,0.00001657196],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978608,0.000566226,0.0007157856,0.00001107429,0.000008345786,0.00001682118,0.0000337859,0.00002001355,0.0007670816],"genre_scores_gemma":[0.9979889,0.000209986,0.001132077,0.00001266385,0.000004222469,0.000008939878,0.00005421641,0.000019395,0.0005696032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001169937,"threshold_uncertainty_score":0.00232625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005586344510385743,"score_gpt":0.2241673076241562,"score_spread":0.2185809631137705,"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."}}