{"id":"W1972089159","doi":"10.2495/hpsm140491","title":"Improving the performance of magnesium alloys for automotive applications","year":2014,"lang":"en","type":"article","venue":"WIT transactions on the built environment","topic":"Magnesium Alloys: Properties and Applications","field":"Materials Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Automotive industry; Magnesium; Automotive engineering; Computer science; Materials science; Metallurgy; Engineering; Aerospace engineering","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":[0.0002197838,0.0005603357,0.0003116181,0.0005117591,0.000213024,0.0005417254,0.0005257798,0.0007130492,0.001857593],"category_scores_gemma":[0.0004202428,0.0001581175,0.000260697,0.0005704464,0.00009317747,0.0004169758,0.0002921032,0.0002339296,0.002428772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003476723,"about_ca_system_score_gemma":0.000169151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007937231,"about_ca_topic_score_gemma":0.001465906,"domain_scores_codex":[0.9998021,0.00001588682,0.0000137412,0.00002311838,0.0001112997,0.00003393046],"domain_scores_gemma":[0.9998988,0.00001010837,0.00002254498,0.000007234556,0.00005060975,0.00001066794],"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":[0.00006684915,0.00002641079,0.0005666058,0.0003290757,0.00001023191,0.000119864,0.00003963432,0.0006338151,0.9642901,0.0004163189,0.0006896841,0.03281126],"study_design_scores_gemma":[0.00001613268,0.0006011136,0.006050854,0.00005692315,0.00006148055,0.000387074,0.00007450279,0.003428838,0.939914,0.0002856076,0.04910512,0.00001821776],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8946123,0.0477163,0.0199778,0.0008424433,0.0003968742,0.00008046554,0.0003803258,0.0008310502,0.03516263],"genre_scores_gemma":[0.9704001,0.008686369,0.01139608,0.0001014802,0.00009504298,0.00002590294,0.0002831032,0.0001254924,0.008886414],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001857593,"threshold_uncertainty_score":0.006214201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01124782546937084,"score_gpt":0.1918995326782782,"score_spread":0.1806517072089074,"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."}}