{"id":"W2778963839","doi":"10.1016/j.addma.2017.12.012","title":"Achieving low surface roughness AlSi10Mg_200C parts using direct metal laser sintering","year":2017,"lang":"en","type":"article","venue":"Additive manufacturing","topic":"Additive Manufacturing Materials and Processes","field":"Engineering","cited_by":98,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; New Brunswick Innovation Foundation","keywords":"Materials science; Direct metal laser sintering; Surface roughness; Porosity; Microstructure; Selective laser sintering; Metallurgy; Surface finish; Aluminium; Sintering; Machining; Laser power scaling; Laser; Composite material; Selective laser melting; Optics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002622098,0.0006378897,0.0006515771,0.0001001886,0.001018949,0.0007389706,0.0006601896,0.0001574875,0.0008579299],"category_scores_gemma":[0.0001141814,0.0006308284,0.0001895058,0.00003549648,0.000169499,0.001238321,0.0003877204,0.0003352001,0.0001384216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001583292,"about_ca_system_score_gemma":0.00002127217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001240113,"about_ca_topic_score_gemma":0.00005060562,"domain_scores_codex":[0.997719,0.00006508762,0.0004429004,0.0006022539,0.0003149693,0.0008557771],"domain_scores_gemma":[0.9985566,0.0001815918,0.0002443195,0.0007650474,0.00005965581,0.0001927586],"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":[0.0003277537,0.0002917636,0.001604999,0.003099526,0.002628827,0.00164878,0.002806402,0.6355693,0.2414809,0.000134285,0.002518805,0.1078887],"study_design_scores_gemma":[0.0003674216,0.0000250382,0.01008944,0.0003992299,0.00007485899,0.00002733149,0.00009249893,0.002048082,0.9774916,0.00009219782,0.008468713,0.0008235681],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9802672,0.0001663194,0.002603174,0.00002327528,0.001663517,0.0002640054,0.0004072051,0.0006033253,0.014002],"genre_scores_gemma":[0.997708,0.0001232352,0.0008257049,0.00003852736,0.0007102979,0.00002175555,0.0000556864,0.0001696564,0.0003471462],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7360107,"threshold_uncertainty_score":0.9996143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01965012679208407,"score_gpt":0.2451829163878183,"score_spread":0.2255327895957342,"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."}}