{"id":"W2962848625","doi":"10.3390/jmmp3030061","title":"Sustainability Assessment during Machining Ti-6Al-4V with Nano-Additives-Based Minimum Quantity Lubrication","year":2019,"lang":"en","type":"article","venue":"Journal of Manufacturing and Materials Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Ontario Tech University","funders":"","keywords":"Lubrication; Machining; Sustainability; Nanofluid; Process (computing); Materials science; Mechanical engineering; Tool wear; Process engineering; Manufacturing engineering; Metallurgy; Computer science; Engineering; Nanotechnology; Nanoparticle","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":[0.0005836819,0.0002498838,0.0002748247,0.0003961174,0.0001728863,0.0004729263,0.000291202,0.0003666862,0.0002241213],"category_scores_gemma":[0.0006491903,0.0001326283,0.0003314975,0.000202248,0.0002940631,0.0004297042,0.0003716507,0.00017267,0.00004617497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004184706,"about_ca_system_score_gemma":0.0003248853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009692439,"about_ca_topic_score_gemma":0.00198302,"domain_scores_codex":[0.9996825,0.00006005366,0.00001646911,0.00003720799,0.0001610757,0.00004265738],"domain_scores_gemma":[0.9997408,0.00009013378,0.0000593513,0.00001448348,0.0000828167,0.00001239887],"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":[0.0006093915,0.0001656314,0.03187217,0.0006589633,0.00006534615,0.0003462599,0.000556082,0.1535682,0.7518666,0.001153237,0.0001143547,0.05902381],"study_design_scores_gemma":[0.00001748534,0.001675461,0.02537726,0.00002970891,0.00006502739,0.0001914078,0.0006368498,0.2774086,0.6916271,0.001382353,0.001547418,0.00004129775],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9862818,0.0002868808,0.01271098,0.00002137677,0.000003472662,0.00001688987,0.00002474715,0.00003451473,0.000619292],"genre_scores_gemma":[0.9965093,0.0000994724,0.003180706,0.000003123765,5.984819e-7,0.000006485543,0.00002441317,0.000003936307,0.0001720635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009692439,"threshold_uncertainty_score":0.003086805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003819239951350127,"score_gpt":0.2322752654588869,"score_spread":0.2284560255075368,"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."}}