{"id":"W2074363025","doi":"10.5539/mas.v9n4p151","title":"Application of Additive Technologies in the Production of Aircraft Engine Parts","year":2015,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Education and Science of the Russian Federation","keywords":"Investment casting; Foundry; Casting; Process engineering; Manufacturing engineering; Rapid prototyping; 3D printing; Molding (decorative); Production (economics); Mold; Ceramic; Computer science; Materials science; Mechanical engineering; Engineering; Metallurgy; Composite material","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006548211,0.0003938926,0.0002698741,0.001171649,0.0003206188,0.0008975035,0.0004240903,0.0003852558,0.001308371],"category_scores_gemma":[0.0008546009,0.0002903673,0.0003873286,0.0009590769,0.0003296353,0.0004007784,0.0003417647,0.000415367,0.0004681375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003562737,"about_ca_system_score_gemma":0.0004164205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008356578,"about_ca_topic_score_gemma":0.001063417,"domain_scores_codex":[0.9988118,0.0001295671,0.00004865605,0.0001008438,0.0008650917,0.00004391848],"domain_scores_gemma":[0.9995571,0.0001410424,0.00005553999,0.00009122671,0.0001416795,0.00001339905],"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":[0.0002312668,0.0001094388,0.00431468,0.00147407,0.00005632488,0.0007088657,0.0003807933,0.03553208,0.551975,0.008477482,0.00066588,0.396074],"study_design_scores_gemma":[0.00002597729,0.002123021,0.01369465,0.0002262705,0.0002121251,0.002684314,0.0002026472,0.0427583,0.8429053,0.002849573,0.09221892,0.00009890846],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4284907,0.05718788,0.4661206,0.000276287,0.0004419827,0.0002584833,0.0002910263,0.0008926993,0.04604029],"genre_scores_gemma":[0.8341273,0.01312368,0.1471759,0.0000415248,0.00006183999,0.00004803402,0.000134211,0.00005568166,0.00523177],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001308371,"threshold_uncertainty_score":0.004376948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01781812593618707,"score_gpt":0.2255002971719123,"score_spread":0.2076821712357252,"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."}}