{"id":"W3141673885","doi":"10.1021/cen-09702-cover15","title":"Tariffs will muddy the waters for automotive materials","year":2019,"lang":"en","type":"article","venue":"C&EN Global Enterprise","topic":"Biotechnology and Related Fields","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Automotive industry; China; Truck; Quarter (Canadian coin); Business; Agency (philosophy); International trade; Service (business); Economics; Commerce; Finance; Marketing; Engineering; Political science; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001620597,0.0001442658,0.0002443434,0.000025784,0.0000638979,0.00001551499,0.0001894427,0.001215627,0.0002925495],"category_scores_gemma":[0.00006398989,0.00008253037,0.0001082517,0.00008865001,0.0001112637,0.00005436022,0.00008551921,0.0004599889,0.0003449036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007737278,"about_ca_system_score_gemma":0.00003916649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003309389,"about_ca_topic_score_gemma":0.000001494365,"domain_scores_codex":[0.9991637,0.00003385392,0.0001887806,0.0002389287,0.00009681816,0.000277872],"domain_scores_gemma":[0.9994432,0.00003294257,0.0000571111,0.0003535346,0.00005609555,0.00005711855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.01875081,0.003097741,0.1221264,0.001807843,0.007561591,0.0006623539,0.01041796,0.0001430763,0.2837397,0.1366761,0.3706776,0.04433879],"study_design_scores_gemma":[0.0169316,0.003792102,0.06508183,0.001161448,0.001439079,0.001004876,0.002578629,0.0006766091,0.1979799,0.008120717,0.7000545,0.001178756],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9519979,0.0002240658,0.0008440762,0.03870362,0.001956524,0.001240061,0.00009697208,0.000207192,0.004729534],"genre_scores_gemma":[0.9938476,0.00008580076,0.0002891098,0.003254784,0.000095248,0.00002787166,0.00003679897,0.00001227654,0.002350499],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3293768,"threshold_uncertainty_score":0.9376026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003099596587434035,"score_gpt":0.2407991359336739,"score_spread":0.2376995393462398,"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."}}