{"id":"W2146595489","doi":"10.1002/cb.252","title":"Neuroethics of neuromarketing","year":2008,"lang":"en","type":"article","venue":"Journal of Consumer Behaviour","topic":"Neuroethics, Human Enhancement, Biomedical Innovations","field":"Neuroscience","cited_by":300,"is_retracted":false,"has_abstract":true,"ca_institutions":"NeuroDevNet; University of British Columbia","funders":"British Columbia Knowledge Development Fund; Dana Foundation; Dana Alliance for Brain Initiatives; Canadian Institutes of Health Research; University of British Columbia; University of Cambridge","keywords":"Neuromarketing; Marketing; Premise; Business; Autonomy; Neuroethics; Advertising; Psychology; Internet privacy; Computer science; Political science; Law; Neuroscience","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007100927,0.0001647453,0.0003480951,0.0003639521,0.0002007065,0.00001961231,0.0005329508,0.00009942014,0.0001929877],"category_scores_gemma":[0.005167563,0.0001510122,0.0001678113,0.0005789039,0.0009222297,0.0002652706,0.0001023493,0.001156706,0.00001751011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002513473,"about_ca_system_score_gemma":0.0002828153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005606698,"about_ca_topic_score_gemma":0.000001064555,"domain_scores_codex":[0.9969359,0.0003691899,0.001182119,0.0002225074,0.001012722,0.0002775601],"domain_scores_gemma":[0.996712,0.001074595,0.00124061,0.0002956588,0.0005191964,0.0001579844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008742189,0.0004946169,0.03451172,0.00003414014,0.00001273446,0.0009724166,0.0003703887,0.000006271877,0.9574998,0.001043046,0.003257724,0.001709729],"study_design_scores_gemma":[0.001988632,0.0007327499,0.1177668,0.0001872535,0.0001398292,0.004399366,0.00006230972,0.00005703107,0.8643755,0.001188642,0.008699601,0.0004023371],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961922,0.00006481375,0.0005443973,0.001233315,0.001051993,0.0001051655,0.0000125166,0.00002334964,0.0007722345],"genre_scores_gemma":[0.9971094,0.0004139667,0.0007259128,0.001362875,0.00009635694,0.000001689346,3.598924e-7,0.00002829891,0.000261156],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09312434,"threshold_uncertainty_score":0.618643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1364129402690837,"score_gpt":0.3366689745422153,"score_spread":0.2002560342731316,"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."}}