{"id":"W31502452","doi":"10.1021/acs.biomac.9b01115","title":"What Appeals to the Chinese Customers? Content Analysis of Chinese Advertisements in Newspaper and on TV","year":2008,"lang":"en","type":"article","venue":"Biomacromolecules","topic":"Globalization and Cultural Identity","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Solvay; Government of Ontario","keywords":"Advertising; Newspaper; Product (mathematics); Psychology; Sociology; Marketing; Business","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001918841,0.00009625508,0.000188025,0.000145388,0.0002211265,0.0000701719,0.000186727,0.00004096591,0.00008342556],"category_scores_gemma":[0.0001570089,0.00005770003,0.00008600001,0.001775098,0.0001503953,0.000182757,0.00005171765,0.00002764395,0.0000201101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003898754,"about_ca_system_score_gemma":0.00001749716,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006210368,"about_ca_topic_score_gemma":0.03346922,"domain_scores_codex":[0.9989856,0.0001426722,0.0001959813,0.0001783959,0.0003348773,0.0001624225],"domain_scores_gemma":[0.9996054,0.00002346687,0.00006920625,0.0001339049,0.00007569374,0.00009238073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005834075,0.0002650281,0.9337936,0.00001014826,0.0003782537,0.00003046933,0.04507343,0.0001694346,0.01226195,0.003540518,0.001526325,0.002892495],"study_design_scores_gemma":[0.0002245636,0.0000207447,0.9934154,0.0000157208,0.0000353257,6.432045e-7,0.00306079,0.00003541222,0.00009457483,0.0000595191,0.002945466,0.00009183285],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99521,0.0004058985,0.00001143283,0.001774963,0.0001644192,0.000217302,0.000009805998,0.00001397889,0.002192204],"genre_scores_gemma":[0.9979287,0.0007104774,0.00001662794,0.0008007197,0.00001999773,0.000009034724,0.00001057591,0.000003298301,0.0005005049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05962181,"threshold_uncertainty_score":0.9841675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03063367877689879,"score_gpt":0.324540755591298,"score_spread":0.2939070768143992,"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."}}