{"id":"W2521835097","doi":"10.5539/ibr.v9n11p38","title":"Customers' Choice between Online or Offline Channel about Search Products, Experience Products and Credence Products","year":2016,"lang":"en","type":"article","venue":"International Business Research","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Credence; Online and offline; Channel (broadcasting); Advertising; Publicity; Selection (genetic algorithm); Marketing; Business; Credence good; Computer science; Information asymmetry; Artificial intelligence; Telecommunications; Machine learning","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":[0.001082744,0.0001765976,0.0002407594,0.0004235535,0.0005080013,0.001377769,0.0001830164,0.0004994146,0.01073145],"category_scores_gemma":[0.004876285,0.0001289391,0.0002040751,0.0002682359,0.0003874091,0.0009727936,0.0003605626,0.0004115627,0.001570679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002102344,"about_ca_system_score_gemma":0.0002093606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008478594,"about_ca_topic_score_gemma":0.001119949,"domain_scores_codex":[0.9993418,0.0002746375,0.0000437391,0.00009176545,0.0001398406,0.0001082157],"domain_scores_gemma":[0.9945226,0.003731211,0.0005066309,0.0002596524,0.0004864213,0.0004935661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00447938,0.003684646,0.8151124,0.0002393724,0.00005376399,0.0008577294,0.01434001,0.000601391,0.02911766,0.002006731,0.003433613,0.1260734],"study_design_scores_gemma":[0.000231419,0.004472619,0.9367488,0.00007176481,0.0001489798,0.0008975877,0.02735484,0.006956546,0.01381248,0.001312387,0.007860934,0.00013156],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976158,0.00002407847,0.0001460338,0.00003357828,0.000004426531,0.00002305415,0.00005542547,0.000006135277,0.002091522],"genre_scores_gemma":[0.9971247,0.00002629578,0.0002866343,0.00004830045,0.000007138476,0.00002228993,0.00007233532,0.000003962391,0.002408348],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01073145,"threshold_uncertainty_score":0.03590029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1569286316097963,"score_gpt":0.4423962207895793,"score_spread":0.285467589179783,"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."}}