{"id":"W2982039664","doi":"10.2139/ssrn.3219972","title":"Identification of Dynamic Games With Unobserved Heterogeneity and Multiple Equilibria: Global Fast Food Chains in China","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Wine Industry and Tourism","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"China; Identification (biology); Econometrics; Economics; Microeconomics; Computer science; Mathematical economics; Biology; Geography","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":[0.002713864,0.0011133,0.002257194,0.001554325,0.001605483,0.003023201,0.001947315,0.00201994,0.004446471],"category_scores_gemma":[0.007712503,0.0007455879,0.001518901,0.001253058,0.002030838,0.003693386,0.002242993,0.001626203,0.000136552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003970567,"about_ca_system_score_gemma":0.004546412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1006139,"about_ca_topic_score_gemma":0.07455441,"domain_scores_codex":[0.9989868,0.000397315,0.00004114466,0.0002047172,0.00007231299,0.0002978404],"domain_scores_gemma":[0.9932059,0.004513049,0.001143087,0.0001765546,0.0003561195,0.0006051791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004543737,0.0002664538,0.03180519,0.0001730861,0.0003360934,0.001120142,0.001186555,0.8593247,0.0006115626,0.09578355,0.001558682,0.007379604],"study_design_scores_gemma":[0.00009780561,0.00005792503,0.004634577,0.00002139593,0.00008887383,0.00003982739,0.0007669032,0.9620916,0.0001345794,0.03168123,0.0003465051,0.00003882873],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9631953,0.0002048201,0.03188684,0.0007763216,0.0000132687,0.0001066095,0.0002442432,0.00003548083,0.003537152],"genre_scores_gemma":[0.9962698,0.0001443318,0.001468463,0.00002786144,0.00001010322,0.00004963061,0.0001358246,0.000007823834,0.001886055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1006139,"threshold_uncertainty_score":0.2000565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00845860813006329,"score_gpt":0.2223046136212925,"score_spread":0.2138460054912292,"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."}}