{"id":"W3102755868","doi":"10.1080/17515831.2020.1838100","title":"Effect of WS <sub>2</sub> particles in cutting fluid on tribological behaviour of Ti–6Al–4V and on its machining performance","year":2020,"lang":"en","type":"article","venue":"Tribology - Materials Surfaces & Interfaces","topic":"Advanced materials and composites","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Materials science; Cutting fluid; Tribology; Enhanced Data Rates for GSM Evolution; Surface roughness; Alloy; Metallurgy; Adhesive wear; Surface finish; Titanium alloy; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002503948,0.0005690468,0.0003359144,0.0002674719,0.0002183078,0.0005725076,0.0002437622,0.0004419692,0.0008963221],"category_scores_gemma":[0.00066131,0.0002971029,0.000212206,0.0002568905,0.0002840399,0.0004663393,0.0002236139,0.0003484287,0.0002130293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002777237,"about_ca_system_score_gemma":0.0002097367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00128024,"about_ca_topic_score_gemma":0.002499715,"domain_scores_codex":[0.9997004,0.00004137437,0.00003373494,0.00006497461,0.00009628649,0.00006323457],"domain_scores_gemma":[0.9995633,0.0001642675,0.0001081681,0.00002570721,0.00009231831,0.0000462544],"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":[0.000239396,0.00001779636,0.0002665363,0.00006294015,0.000008985653,0.00004534667,0.00003039268,0.0001449224,0.997776,0.00001909178,0.00001507195,0.001373444],"study_design_scores_gemma":[0.000005127778,0.0001900166,0.001268651,0.000002870607,0.00001256257,0.00002579753,0.00001924449,0.0004467998,0.9976562,0.000004922225,0.0003621345,0.000005581071],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984453,0.0004792735,0.0005461606,0.00001430689,0.00001614621,0.00001173318,0.00006120427,0.00002818057,0.0003976432],"genre_scores_gemma":[0.9972141,0.0003197015,0.001838524,0.00001763178,0.000009099331,0.00001287434,0.00005847856,0.00002230622,0.0005071293],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00128024,"threshold_uncertainty_score":0.002998531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01601357550324972,"score_gpt":0.2438738500517338,"score_spread":0.2278602745484841,"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."}}