{"id":"W2025504884","doi":"10.1007/s11837-013-0677-1","title":"Process Modeling of Low-Pressure Die Casting of Aluminum Alloy Automotive Wheels","year":2013,"lang":"en","type":"article","venue":"JOM","topic":"Aluminum Alloy Microstructure Properties","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Automotive industry; Process (computing); Casting; Die casting; Mechanical engineering; Automotive engineering; Component (thermodynamics); Manufacturing engineering; Aluminium; Die (integrated circuit); Engineering; Materials science; Computer science; Metallurgy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002309817,0.0004219454,0.0007538103,0.0004330532,0.0005575622,0.0008265841,0.001118147,0.0009903309,0.002707713],"category_scores_gemma":[0.0003810779,0.0004259215,0.0006446277,0.0003218588,0.0003262286,0.0003781304,0.000254908,0.0003904555,0.0005499164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001097405,"about_ca_system_score_gemma":0.001484129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02850534,"about_ca_topic_score_gemma":0.02366154,"domain_scores_codex":[0.9998848,0.00001349902,0.000003995612,0.00001466018,0.000056918,0.00002590486],"domain_scores_gemma":[0.9998485,0.00005149144,0.00002413645,0.00001364931,0.0000528187,0.000009316567],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002450931,0.0000303118,0.0005447337,0.00004505025,0.000008005157,0.00006219686,0.00002289614,0.9883604,0.006443182,0.001482882,0.000106375,0.002869536],"study_design_scores_gemma":[0.00000340878,0.00001243751,0.0002868232,0.000002329266,0.000003501248,0.000007588914,0.000006465811,0.9974362,0.001801168,0.000114585,0.0003226725,0.000002794459],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6987308,0.001267315,0.2484404,0.0002296194,0.00009153685,0.0001565226,0.0009821891,0.0009416551,0.04916003],"genre_scores_gemma":[0.9829853,0.0003322121,0.00857972,0.00001478934,0.000007637393,0.0000572116,0.0002162688,0.00007227591,0.007734705],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02850534,"threshold_uncertainty_score":0.05667883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009012785934049309,"score_gpt":0.2014037352763982,"score_spread":0.1923909493423489,"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."}}