{"id":"W6961585969","doi":"10.14288/1.0375864","title":"Automobile Industrie","year":2017,"lang":"en","type":"article","venue":"Open Collections","topic":"Merger and Competition Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Automotive industry; German; Production (economics); Product (mathematics); Process (computing)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001568039,0.0002809043,0.0001881425,0.003065255,0.001679125,0.001766596,0.0004348149,0.0005119716,0.02177653],"category_scores_gemma":[0.0006361106,0.0001852812,0.000316126,0.003249633,0.00038722,0.0006981748,0.0006205087,0.0006788022,0.003801589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00908341,"about_ca_system_score_gemma":0.007636328,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.8919745,"about_ca_topic_score_gemma":0.9517081,"domain_scores_codex":[0.9993576,0.00001402998,0.00001470525,0.00008386951,0.0003251732,0.0002046286],"domain_scores_gemma":[0.9995099,0.00003565038,0.00007318304,0.00001525858,0.0002701117,0.00009591825],"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":[0.0008475501,0.0003204732,0.268876,0.0005782099,0.0002241988,0.00264625,0.003743952,0.001522375,0.004299054,0.03871357,0.4946351,0.1835934],"study_design_scores_gemma":[0.00001364124,0.00005123654,0.6530277,0.00005668345,0.00003332744,0.0002161851,0.002680284,0.0005545269,0.001236339,0.0005116457,0.3415942,0.00002424033],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.4578938,0.006274302,0.0004687691,0.002143637,0.0002680061,0.0001718449,0.09022186,0.0002444938,0.4423133],"genre_scores_gemma":[0.5111362,0.001770566,0.0002650673,0.0002838277,0.00005094425,0.00002778739,0.02849268,0.00004959712,0.4579234],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8919745,"threshold_uncertainty_score":0.2173233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0634706468366208,"score_gpt":0.2686852677448432,"score_spread":0.2052146209082224,"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."}}