{"id":"W2759085868","doi":"10.1007/s00170-017-1088-1","title":"Coolant strategy influence on tool life and surface roughness when machining ADI","year":2017,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":57,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Tech University; University of Guelph","funders":"","keywords":"Machinability; Austempering; Materials science; Microstructure; Machining; Austenite; Ferrite (magnet); Metallurgy; Coolant; Surface roughness; Carbide; Tool wear; Composite material; Mechanical engineering; Bainite","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001563212,0.0001543626,0.0001865808,0.0001219843,0.0001987555,0.0001411478,0.0009959437,0.00008070634,0.000009205637],"category_scores_gemma":[0.0002645369,0.0001160926,0.00003217254,0.00002018272,0.0001104873,0.0005357049,0.0001500375,0.000477579,0.000002686902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000058686,"about_ca_system_score_gemma":0.00002450349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005034471,"about_ca_topic_score_gemma":0.00000574727,"domain_scores_codex":[0.9991712,0.000007692572,0.0003070814,0.0001236274,0.0002224491,0.0001679803],"domain_scores_gemma":[0.9991238,0.00008530492,0.000357908,0.0002685166,0.0001245096,0.00003995628],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009706498,0.00000894695,0.00028437,0.00001243771,0.00007551334,0.00003125346,0.00008134456,0.9489072,0.00255592,0.001806128,0.00002408244,0.04611573],"study_design_scores_gemma":[0.007693425,0.001172699,0.04068563,0.001702196,0.000145877,0.00169209,0.001345859,0.1076288,0.6200045,0.1974278,0.01867589,0.001825232],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9803169,0.0003892122,0.01673669,0.001545474,0.000529378,0.00006571619,0.000005148845,0.0001075562,0.0003038889],"genre_scores_gemma":[0.9907212,0.0008459996,0.008184043,0.0001056417,0.00008458871,0.000002265038,0.000001080192,0.00002377506,0.00003143831],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8412784,"threshold_uncertainty_score":0.473412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008959068563510888,"score_gpt":0.2539939620169222,"score_spread":0.2450348934534113,"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."}}