{"id":"W3129817463","doi":"","title":"Regional Resilience and the Future of Ontario’s Automotive Sector in the Age of Digital Disruption","year":2019,"lang":"en","type":"article","venue":"","topic":"Regional resilience and development","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Automotive industry; Original equipment manufacturer; Digitization; Modernization theory; Business; Industrial organization; Service (business); Marketing; Engineering; Economics; Economic growth; Telecommunications; Computer science","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":[0.0003645949,0.00006237756,0.0001873484,0.00006633197,0.00002101744,0.00002370851,0.0001845505,0.00003485605,0.00006234992],"category_scores_gemma":[0.00003176458,0.00003514775,0.00005046407,0.0001581844,0.00016819,0.0001741649,0.00003455605,0.00007125058,0.00002586131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002323566,"about_ca_system_score_gemma":0.00002394052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003011198,"about_ca_topic_score_gemma":0.0002030853,"domain_scores_codex":[0.9993724,0.00001105262,0.0003002849,0.0001575113,0.00006688174,0.00009192733],"domain_scores_gemma":[0.9995141,0.0001440516,0.0001472626,0.0001626135,0.00002057736,0.00001139191],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00007237931,0.00004548714,0.4324902,0.00001550952,0.00001102065,0.000001197692,0.003553821,0.00005231666,0.0000115322,0.5627989,0.000310878,0.0006367109],"study_design_scores_gemma":[0.0005897814,0.00004471207,0.949448,0.00001325456,0.000001009369,0.000003987262,0.001745014,0.0002018917,0.00001999225,0.04077146,0.007095667,0.00006524933],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9754916,0.0005735934,0.0001531314,0.001794705,0.0000613525,0.0002125087,0.00001033135,0.00000222658,0.02170048],"genre_scores_gemma":[0.9984124,0.0002028004,0.00007528973,0.0002474546,0.00001694341,0.00000633235,0.000005504435,0.000002455973,0.001030848],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5220274,"threshold_uncertainty_score":0.1433284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01852111067606321,"score_gpt":0.2136903374779857,"score_spread":0.1951692268019225,"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."}}