{"id":"W2394731750","doi":"10.5539/ijms.v8n3p129","title":"Predictors of Attitudinal Outcomes in Mobile Advertising in Sri Lanka: An Emerging Market","year":2016,"lang":"en","type":"article","venue":"International Journal of Marketing Studies","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Advertising; Demographics; Sri lanka; Mobile marketing; Business; Mobile internet; The Internet; Marketing; Developing country; Online advertising; Digital marketing; Economics; Economic growth; Sociology; Computer science; Socioeconomics; Demography","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":[0.0007051938,0.0001719677,0.0001559834,0.0008719524,0.0005385546,0.001503476,0.0002719201,0.0003775359,0.002306786],"category_scores_gemma":[0.001683361,0.0001469057,0.0003473134,0.001031982,0.0004414509,0.0004260174,0.0005226536,0.001033989,0.0004462228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003708567,"about_ca_system_score_gemma":0.0004497945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01752812,"about_ca_topic_score_gemma":0.02355924,"domain_scores_codex":[0.9997092,0.00006926103,0.00003191467,0.00003362937,0.00006923527,0.00008669204],"domain_scores_gemma":[0.9980128,0.0003643208,0.0008099687,0.0000684245,0.0003007028,0.0004437606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002361172,0.00008794951,0.9978799,0.000006969509,0.00001484329,0.000113032,0.0006370759,0.00001563331,0.0001019843,0.000039943,0.00008366565,0.0009953771],"study_design_scores_gemma":[0.000001453517,0.00005252438,0.9966857,0.000006737441,0.00001144141,0.00009060578,0.002830941,0.0001186443,0.00003757642,0.00001234416,0.0001483893,0.000003584123],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989582,0.00004336746,0.000008638169,0.00005764931,0.00000169486,0.000004845712,0.00007056359,9.253744e-7,0.000854081],"genre_scores_gemma":[0.9995607,0.00006580194,0.00002033275,0.00002021974,0.000003515739,0.000003786224,0.0001197067,8.473788e-7,0.0002051084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01752812,"threshold_uncertainty_score":0.03485221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02666240937917166,"score_gpt":0.3764055455187945,"score_spread":0.3497431361396228,"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."}}