{"id":"W3011389656","doi":"10.1109/access.2020.2979855","title":"EEG-Based Neurohaptics Research: A Literature Review","year":2020,"lang":"en","type":"review","venue":"IEEE Access","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University; New York University Abu Dhabi","keywords":"Electroencephalography; Computer science; Kinesthetic learning; Field (mathematics); Domain (mathematical analysis); Virtual reality; Haptic technology; Human–computer interaction; Artificial intelligence; Data science; Psychology; Neuroscience; Mathematics education","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0006624085,0.0006502557,0.001933042,0.0003872941,0.0002215775,0.001343055,0.004467617,0.0003223372,0.00008075005],"category_scores_gemma":[0.001701392,0.0004724037,0.0006577822,0.00327146,0.0002072966,0.0004238318,0.0005852917,0.002576146,0.0006091114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007773731,"about_ca_system_score_gemma":0.0004881354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002850097,"about_ca_topic_score_gemma":0.00000125612,"domain_scores_codex":[0.9940196,0.001926692,0.0008565822,0.001440226,0.001045963,0.0007109821],"domain_scores_gemma":[0.9958048,0.002199182,0.0004039956,0.001090768,0.0001971332,0.0003040638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000004778287,0.00006771341,1.177712e-7,0.1529593,0.00001523538,0.001452037,0.00003472281,0.000001565583,0.00002626523,0.0001628688,0.1053331,0.7399423],"study_design_scores_gemma":[0.00006689617,0.00007902704,4.988332e-8,0.1611368,0.0001086826,0.0001152456,3.090797e-7,0.00007511986,0.0002336005,0.00004863302,0.8377738,0.0003618574],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[6.967779e-7,0.9931256,0.0001377637,0.001350341,0.001453171,0.001623937,0.0001770636,0.0002135101,0.001917918],"genre_scores_gemma":[0.00001290386,0.9896667,0.00005758918,0.008775187,0.0006497494,0.0001878139,0.00002578689,0.0001146126,0.0005096635],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.7395804,"threshold_uncertainty_score":0.9997728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3451260733842431,"score_gpt":0.4869869959177233,"score_spread":0.1418609225334801,"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."}}