{"id":"W4307637833","doi":"10.2478/nimmir-2022-0013","title":"Consumer Experiences with Marketing Technology: Solving the Tensions Between Benefits and Costs","year":2022,"lang":"en","type":"article","venue":"NIM Marketing Intelligence Review","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Variety (cybernetics); Publishing; Publication; Marketing; Public relations; Business; Library science; Sociology; Advertising; Political science; Computer science; Law","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":[0.005741091,0.0002618034,0.0004728695,0.0009344727,0.00115477,0.006623125,0.0005016513,0.002607067,0.005282619],"category_scores_gemma":[0.009830171,0.0002035581,0.000283136,0.001325145,0.00262749,0.006899897,0.002149028,0.003204918,0.0005467101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001629683,"about_ca_system_score_gemma":0.0009527204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001352101,"about_ca_topic_score_gemma":0.001974934,"domain_scores_codex":[0.9954034,0.003113094,0.0001052032,0.0001324012,0.001061705,0.0001841319],"domain_scores_gemma":[0.9920571,0.006220683,0.000451783,0.0001483987,0.0007656991,0.0003562742],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003415791,0.0003610751,0.008997352,0.005415807,0.0002667942,0.0017393,0.1882335,0.0002757826,0.002019773,0.09198767,0.08549919,0.6148622],"study_design_scores_gemma":[0.00004417238,0.0002677894,0.01067854,0.006168067,0.0001001204,0.001730196,0.1332247,0.0002950395,0.0007110788,0.01959273,0.8271145,0.00007305484],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.2826265,0.3224501,0.00599983,0.1877106,0.001686083,0.0001287199,0.0001298268,0.00009057748,0.1991777],"genre_scores_gemma":[0.760325,0.1941778,0.002783934,0.02756549,0.001439755,0.000122856,0.0001043423,0.00007099602,0.01340991],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006623125,"threshold_uncertainty_score":0.03036213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03877848251334326,"score_gpt":0.313048493634015,"score_spread":0.2742700111206717,"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."}}