{"id":"W3136994693","doi":"10.1109/tcds.2021.3065200","title":"A Survey on Neuromarketing Using EEG Signals","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Cognitive and Developmental Systems","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Army Research Office","keywords":"Neuromarketing; Computer science; Electroencephalography; Functional magnetic resonance imaging; Process (computing); Product (mathematics); Artificial intelligence; Human–computer interaction; Data science; Neuroscience; Psychology","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":[0.001800831,0.001086766,0.0009891541,0.006251708,0.0003141431,0.001889824,0.001060859,0.001537681,0.007506761],"category_scores_gemma":[0.005622787,0.0005025798,0.00092633,0.008014552,0.0003861996,0.00337972,0.0006355597,0.0007626147,0.004980528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003621801,"about_ca_system_score_gemma":0.0006047687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001112067,"about_ca_topic_score_gemma":0.001160419,"domain_scores_codex":[0.9986572,0.0002764271,0.0002154281,0.000230751,0.0005550749,0.00006493201],"domain_scores_gemma":[0.9932871,0.004169664,0.0004842152,0.0002114244,0.001710413,0.0001372037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001922474,0.00007696115,0.004975842,0.006601001,0.0001056913,0.0001879144,0.0001199141,0.0004305578,0.002775059,0.001225294,0.02756817,0.9557415],"study_design_scores_gemma":[0.00005249001,0.0007135514,0.0540402,0.0108273,0.0004718601,0.008179374,0.001044524,0.003043918,0.008384841,0.004119263,0.9088979,0.0002247686],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01480256,0.9029177,0.03945158,0.004632594,0.001495068,0.0002760075,0.002329343,0.0007810066,0.03331427],"genre_scores_gemma":[0.02718812,0.9435408,0.01241331,0.002328105,0.001857075,0.0002139676,0.00279029,0.0001130865,0.009555281],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.007506761,"threshold_uncertainty_score":0.02511263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08177045781237519,"score_gpt":0.2942505910659309,"score_spread":0.2124801332535557,"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."}}