{"id":"W3097491851","doi":"10.3390/ma13215011","title":"Machining of Titanium Metal Matrix Composites: Progress Overview","year":2020,"lang":"en","type":"review","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Polytechnique Montréal","funders":"","keywords":"Machining; Materials science; Tool wear; Grinding; Surface roughness; Chip formation; Adiabatic shear band; Titanium alloy; Metallurgy; Surface finish; Lubrication; Titanium; Composite material; Cutting tool; Shear (geology); Alloy","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":[0.001571551,0.001039685,0.0007885619,0.002649151,0.0004218889,0.001660304,0.001032338,0.001251711,0.002639986],"category_scores_gemma":[0.0007963697,0.0008201044,0.0006938534,0.002768274,0.0004704001,0.001858548,0.0008039546,0.001686784,0.001713839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007611561,"about_ca_system_score_gemma":0.001362737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001992731,"about_ca_topic_score_gemma":0.001571346,"domain_scores_codex":[0.9994735,0.00006647516,0.00005622166,0.0001423547,0.0001859181,0.00007552525],"domain_scores_gemma":[0.9993667,0.0001989239,0.00008629105,0.00003966246,0.0002567649,0.00005169271],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001739696,0.0004416997,0.001160015,0.01902275,0.0001538775,0.000259181,0.0004113813,0.003763372,0.03420873,0.009743958,0.009761727,0.9208993],"study_design_scores_gemma":[0.00002552329,0.001402952,0.004826319,0.003141209,0.0002204676,0.001931382,0.0003825508,0.003984093,0.03731285,0.003295147,0.9433696,0.0001078219],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.005790806,0.9753706,0.0080517,0.0003526435,0.0002925122,0.00005020887,0.00006027955,0.0001018328,0.009929338],"genre_scores_gemma":[0.02073838,0.9601848,0.01316707,0.0002725495,0.0005837718,0.00005902485,0.0002503245,0.00004442404,0.004699723],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002649151,"threshold_uncertainty_score":0.00883162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0343419547927369,"score_gpt":0.3355540046326184,"score_spread":0.3012120498398815,"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."}}