{"id":"W7162716473","doi":"","title":"Recent Trends in the Canadian Automobile Industry after the Lehman Shock","year":2019,"lang":"ja","type":"article","venue":"Institutional Repositories DataBase (IRDB)","topic":"Merger and Competition Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Automotive industry; Shock (circulatory); Shock absorber; Auto industry","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":[0.001388651,0.000400932,0.0003831632,0.008373403,0.00227726,0.004761482,0.001510675,0.00165559,0.006877531],"category_scores_gemma":[0.007733859,0.0002214103,0.0005226209,0.02031923,0.001274394,0.001362137,0.0009883987,0.001457239,0.0009263491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05661681,"about_ca_system_score_gemma":0.03872835,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9863957,"about_ca_topic_score_gemma":0.993112,"domain_scores_codex":[0.9980245,0.00005599092,0.00009645124,0.0001539032,0.001038136,0.0006310319],"domain_scores_gemma":[0.9846544,0.0006302676,0.002309339,0.0001229083,0.01068728,0.001595748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008533458,0.0002253665,0.7948884,0.0005914218,0.0002280228,0.0008171002,0.002758141,0.00363351,0.001444032,0.01222061,0.07679844,0.1055417],"study_design_scores_gemma":[0.000005690831,0.00002413471,0.9594245,0.00005892038,0.00003509828,0.00007596065,0.002339726,0.0007087543,0.0002582614,0.0001538822,0.03687754,0.00003759246],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8584922,0.01705373,0.0007604067,0.02682707,0.0003710357,0.00008089552,0.03433236,0.000206092,0.06187619],"genre_scores_gemma":[0.9655932,0.007408099,0.0003739145,0.001795003,0.000258644,0.00001337632,0.01174159,0.00003248093,0.01278369],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05661681,"threshold_uncertainty_score":0.4107857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02315483663076847,"score_gpt":0.2369595928006878,"score_spread":0.2138047561699193,"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."}}