{"id":"W3046406968","doi":"","title":"When and how to advertise? An empirical study on mobile ad response based on contextual factors","year":2020,"lang":"en","type":"article","venue":"Journal of the Association for Information Systems","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Empirical research; Advertising; Business; Mathematics; Statistics","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":[0.004059881,0.0001645302,0.0002415951,0.0006851302,0.0007108936,0.001910362,0.0004082102,0.0006718929,0.002203797],"category_scores_gemma":[0.02257882,0.0002365241,0.0002263215,0.001004319,0.000897731,0.00133798,0.0006826964,0.0009640796,0.0003232367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006460595,"about_ca_system_score_gemma":0.0006583275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004786341,"about_ca_topic_score_gemma":0.006820604,"domain_scores_codex":[0.9973071,0.001790936,0.000170822,0.0002284927,0.0003002919,0.0002023218],"domain_scores_gemma":[0.967436,0.02661478,0.002808435,0.0005768438,0.001960513,0.000603404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006406096,0.001772298,0.8292878,0.0005688231,0.0001223503,0.00074206,0.1134854,0.0003541945,0.002955805,0.003307297,0.0007859835,0.0459774],"study_design_scores_gemma":[0.00003259739,0.0006865633,0.7679344,0.0002037418,0.0001485052,0.0003875196,0.219394,0.001945079,0.001477987,0.0007174596,0.007024403,0.00004774646],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968488,0.000107894,0.0001549766,0.0001425203,0.000003727202,0.0000334143,0.00002733619,0.000001102861,0.0026803],"genre_scores_gemma":[0.9987685,0.0001782718,0.0003505102,0.000078012,0.000004578836,0.00002632098,0.00002788687,0.000002542241,0.000563447],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004786341,"threshold_uncertainty_score":0.02147096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03935887468639118,"score_gpt":0.3230850472772679,"score_spread":0.2837261725908767,"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."}}