{"id":"W2082970698","doi":"10.2351/1.3622200","title":"Direct manufacturing of net-shape functional components/test-pieces for aerospace, automotive, and other applications","year":2011,"lang":"en","type":"article","venue":"Journal of Laser Applications","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Aerospace; Near net shape; Materials science; Mechanical engineering; Machining; Automotive industry; Consolidation (business); Impeller; CAD; Process (computing); Rapid prototyping; Engineering drawing; Manufacturing engineering; Computer science; Engineering; Aerospace engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001315227,0.0001262553,0.0002042342,0.0001512811,0.00009506632,0.00001402899,0.0001847058,0.00006986854,0.00005346396],"category_scores_gemma":[0.00002412358,0.0001141666,0.00008221788,0.00008289289,0.0001078986,0.00008639148,0.00003806753,0.0001476717,0.000006952701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002380667,"about_ca_system_score_gemma":0.00001059275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003949596,"about_ca_topic_score_gemma":0.000003233009,"domain_scores_codex":[0.9993152,0.000007311656,0.0003219897,0.0001173733,0.0001026004,0.0001355268],"domain_scores_gemma":[0.9992398,0.0002016925,0.0002094252,0.000181238,0.0001145013,0.00005333675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005875968,0.005417118,0.0960102,0.004571351,0.006007702,0.00001377158,0.005147356,0.05241528,0.09248704,0.03204991,0.07885551,0.6264372],"study_design_scores_gemma":[0.0008272394,0.0001335675,0.07886959,0.00008678943,0.0001636174,0.00004326275,0.0003207951,0.001875004,0.6937608,0.006220096,0.2173494,0.0003498539],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3642771,0.0006788877,0.6255196,0.0002765303,0.0001522183,0.001089853,0.0004022601,0.0005342601,0.007069334],"genre_scores_gemma":[0.978861,0.00007054834,0.02063172,0.00002039221,0.0001039485,0.0002009786,0.000006810004,0.00002579484,0.00007880168],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6260873,"threshold_uncertainty_score":0.4655579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03143852952876024,"score_gpt":0.2270464589287163,"score_spread":0.195607929399956,"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."}}