{"id":"W1800401028","doi":"10.5539/ibr.v8n8p150","title":"Optimizing Digital Marketing for Generation Y: An Investigation of Developing Online Market in Bangladesh","year":2015,"lang":"en","type":"article","venue":"International Business Research","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Advertising; Context (archaeology); The Internet; Social media; Digital marketing; Marketing; Digital media; Business; Online advertising; Order (exchange); Product (mathematics); Habit; Computer science; Geography; Psychology; World Wide Web; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.006463523,0.00007056673,0.0001181958,0.0003722451,0.0001423268,0.0003246679,0.0003409089,0.00008921935,0.0000194828],"category_scores_gemma":[0.01547076,0.00007761548,0.00002442815,0.0007531242,0.000245528,0.001081655,0.00007993321,0.000122273,0.0000019227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003985923,"about_ca_system_score_gemma":0.0009125221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00073014,"about_ca_topic_score_gemma":0.001561186,"domain_scores_codex":[0.9977936,0.0004212809,0.0003031361,0.0002154533,0.0009879255,0.0002785835],"domain_scores_gemma":[0.9961896,0.0009335871,0.00008794974,0.00007804298,0.00259551,0.0001153331],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002103545,0.0007548659,0.5828502,0.0003088385,0.0001161806,0.00003338396,0.07800148,0.001479443,0.003568621,0.02687811,0.01385945,0.2900459],"study_design_scores_gemma":[0.005143477,0.0002422132,0.7305441,0.002013315,0.00001416482,0.000005262786,0.09292024,0.04831339,0.0009511412,0.04280828,0.07571351,0.001330913],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9743508,0.0000338243,0.0006785566,0.004035493,0.0005639983,0.0003056904,0.00004132064,0.00002894776,0.01996143],"genre_scores_gemma":[0.9919772,0.00003006741,0.00586096,0.00003359067,0.0008993762,0.00004146703,0.0002586422,0.00001412991,0.0008845419],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.288715,"threshold_uncertainty_score":0.9928223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1961791894918768,"score_gpt":0.4248419639169251,"score_spread":0.2286627744250483,"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."}}