{"id":"W4393390974","doi":"10.5539/ass.v20n2p75","title":"Research on Brand Equity of Intelligent Connected Vehicles in China","year":2024,"lang":"en","type":"article","venue":"Asian Social Science","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Brand equity; Business; Equity (law); Advertising; Marketing; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001227533,0.0002010297,0.0002052138,0.001636546,0.001405141,0.001338227,0.0002952655,0.0003773104,0.002802934],"category_scores_gemma":[0.001862841,0.0001175788,0.0003700434,0.001920562,0.0007973125,0.001103371,0.000798851,0.0004726703,0.00007461134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002641979,"about_ca_system_score_gemma":0.001917546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03182722,"about_ca_topic_score_gemma":0.03331634,"domain_scores_codex":[0.9995089,0.00007658677,0.00003026679,0.00007584351,0.0001859574,0.0001224453],"domain_scores_gemma":[0.9985785,0.00036912,0.0005158659,0.00006584181,0.0002590001,0.0002115816],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006820587,0.000160264,0.9380037,0.00007092241,0.00006007723,0.0002533443,0.01187706,0.0003396784,0.0005345175,0.01031771,0.0004662926,0.03784836],"study_design_scores_gemma":[0.000005015394,0.00007697658,0.9835172,0.00004684047,0.00004829192,0.00006867103,0.0101989,0.001580882,0.0003003907,0.001658876,0.002483997,0.00001400656],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957016,0.0001739005,0.00007851732,0.0002081553,0.000005575764,0.000005690717,0.00002137203,8.979238e-7,0.003804251],"genre_scores_gemma":[0.9994461,0.0000919157,0.00002561107,0.00002164387,0.000003012489,0.00000197811,0.00001899934,3.318395e-7,0.0003904043],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03182722,"threshold_uncertainty_score":0.06328392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0841378626453444,"score_gpt":0.4541187780265199,"score_spread":0.3699809153811755,"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."}}