{"id":"W3110254642","doi":"10.18280/ria.340515","title":"An Evaluation Strategy for Commercial Precision Marketing Based on Artificial Neural Network","year":2020,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Principal component analysis; Computer science; MATLAB; The Internet; Cluster analysis; Principal (computer security); Data mining; Index (typography); Marketing research; Value (mathematics); Artificial intelligence; Machine learning; Marketing; Business; World Wide Web","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":[0.002432767,0.001165947,0.0008436048,0.002922365,0.0007897587,0.002701517,0.001087977,0.0009868264,0.002934773],"category_scores_gemma":[0.004020129,0.0003311517,0.0006394035,0.001748569,0.0005774216,0.002895736,0.0009861102,0.0005677831,0.0003574333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002566194,"about_ca_system_score_gemma":0.001423357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009317641,"about_ca_topic_score_gemma":0.006412106,"domain_scores_codex":[0.9977289,0.0005945635,0.0002088842,0.0003483292,0.0009366508,0.0001827221],"domain_scores_gemma":[0.9987265,0.0003077124,0.0001224741,0.00005062824,0.0007422297,0.00005042923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007392447,0.0004353258,0.01697756,0.000453301,0.0002844897,0.000285889,0.0003953196,0.4291351,0.01142642,0.01825151,0.005598537,0.5160173],"study_design_scores_gemma":[0.00002311492,0.000118672,0.002395684,0.00002296507,0.00006091196,0.00003867822,0.0001038362,0.990493,0.003161544,0.002597207,0.0009579777,0.0000264436],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.189181,0.001616986,0.7771313,0.0008747746,0.0001777823,0.0007055096,0.0002215268,0.001148392,0.02894294],"genre_scores_gemma":[0.927324,0.0004676832,0.0676071,0.0001074705,0.0000434417,0.0003025127,0.0001780082,0.00004209763,0.003927658],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009317641,"threshold_uncertainty_score":0.01861906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1478113581758519,"score_gpt":0.3761885446972185,"score_spread":0.2283771865213666,"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."}}