{"id":"W3018781214","doi":"10.1016/j.vacuum.2020.109314","title":"Internal surface roughness enhancement of parts made by laser powder-bed fusion additive manufacturing","year":2020,"lang":"en","type":"article","venue":"Vacuum","topic":"Additive Manufacturing Materials and Processes","field":"Engineering","cited_by":78,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; FedDev Ontario; King Fahd University of Petroleum and Minerals","keywords":"Fusion; Materials science; Surface roughness; Electropolishing; Surface finish; Inconel; Laser; Inconel 625; Work (physics); Composite material; Optics; Microstructure; Mechanical engineering; Electrode; Chemistry; Alloy; Physics","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":[0.0001878001,0.0002712247,0.0003256177,0.000351967,0.000198022,0.00045036,0.0002884191,0.0003089881,0.0008513843],"category_scores_gemma":[0.0003326103,0.0001956394,0.0004354826,0.0003073695,0.00025084,0.0002546718,0.0002105628,0.0003160452,0.0001829509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002579213,"about_ca_system_score_gemma":0.0001258143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003822032,"about_ca_topic_score_gemma":0.0005511046,"domain_scores_codex":[0.999744,0.00001829015,0.000009743721,0.00003276738,0.0001366254,0.00005858863],"domain_scores_gemma":[0.9997949,0.00005277852,0.00004739792,0.0000283186,0.00006369279,0.00001297955],"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":[0.0000802299,0.00001126923,0.0002743945,0.00003940241,0.000006595067,0.0000292561,0.00003881622,0.0005341111,0.9948873,0.0001289261,0.00005807443,0.003911544],"study_design_scores_gemma":[0.000003908556,0.00016737,0.004429706,0.00000242327,0.00001802606,0.00005339962,0.00003373458,0.002563302,0.9922224,0.00002299979,0.0004753618,0.000007561408],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940315,0.0006702765,0.003723333,0.00001997923,0.00002622866,0.000005318117,0.00003444985,0.00007886362,0.001410095],"genre_scores_gemma":[0.9982439,0.00009648276,0.001165782,0.000006327599,0.000003844322,0.000002474962,0.00002461128,0.00001062317,0.0004460624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008513843,"threshold_uncertainty_score":0.002848208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01124268265952892,"score_gpt":0.208932193706882,"score_spread":0.1976895110473531,"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."}}