{"id":"W3148295266","doi":"10.1111/poms.13419","title":"The Effect of Tightening Standards on Automakers’ Non‐compliance","year":2021,"lang":"en","type":"article","venue":"Production and Operations Management","topic":"Regulation and Compliance Studies","field":"Business, Management and Accounting","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Compliance (psychology); Competitor analysis; Regression discontinuity design; Business; Industrial organization; Economics; Marketing","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":[0.01517367,0.0002165445,0.0003971997,0.001165135,0.0007652802,0.002043525,0.0007309852,0.001464246,0.003327932],"category_scores_gemma":[0.08318273,0.0002459916,0.0007030516,0.001638745,0.001230969,0.001513617,0.00189762,0.002142067,0.0003380585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001693095,"about_ca_system_score_gemma":0.002284775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007257297,"about_ca_topic_score_gemma":0.006253432,"domain_scores_codex":[0.9770417,0.01070318,0.002135583,0.002552985,0.005300888,0.002265656],"domain_scores_gemma":[0.7756253,0.1050818,0.09505792,0.0121237,0.009322662,0.002788706],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003614486,0.0006080111,0.9382085,0.0001357268,0.0003849813,0.0001944571,0.001328516,0.006377335,0.001543638,0.005971557,0.00104783,0.04383795],"study_design_scores_gemma":[0.0000231723,0.0004010703,0.9872562,0.0000538004,0.00009405291,0.00006079333,0.001377942,0.003693718,0.001565406,0.002681547,0.00276267,0.00002967465],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9890406,0.0004241808,0.002305381,0.001137665,0.000028947,0.000037102,0.0001525147,0.00004382871,0.006829802],"genre_scores_gemma":[0.9990068,0.00005794608,0.0002567667,0.00011267,0.00001693969,0.00001172571,0.00007195753,0.00000362851,0.0004615458],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01517367,"threshold_uncertainty_score":0.08024704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01513698702976384,"score_gpt":0.2644843090155887,"score_spread":0.2493473219858248,"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."}}