{"id":"W4313205000","doi":"10.1016/j.dib.2022.108847","title":"Outdoor walking: Mobile EEG dataset from walking during oddball task and walking synchronization task","year":2022,"lang":"en","type":"article","venue":"Data in Brief","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Deutscher Akademischer Austauschdienst","keywords":"Metronome; Task (project management); Electroencephalography; Psychology; Synchronization (alternating current); Oddball paradigm; Physical medicine and rehabilitation; Computer science; Cognitive psychology; Rhythm; Neuroscience; Medicine; Event-related potential","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"],"consensus_categories":[],"category_scores_codex":[0.0005066413,0.0002501842,0.0002762482,0.0001765926,0.0005092847,0.0003507142,0.001618232,0.0000557493,0.0003005573],"category_scores_gemma":[0.000361392,0.0002712829,0.00002229558,0.0004205637,0.00009975491,0.001050066,0.004108334,0.0004554657,0.00002185434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001218425,"about_ca_system_score_gemma":0.00004140244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000635899,"about_ca_topic_score_gemma":0.0001176635,"domain_scores_codex":[0.996975,0.0003352267,0.0004478192,0.001291115,0.0004816301,0.0004691753],"domain_scores_gemma":[0.9979311,0.0004422275,0.0001915008,0.001329824,0.00001288869,0.0000924542],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002462406,0.0008078042,0.01293382,0.000308189,0.00006855673,0.001318506,0.01070753,0.003187993,0.8050383,0.0003746366,0.05427172,0.1107367],"study_design_scores_gemma":[0.005121492,0.0004406199,0.03742691,0.0005000102,0.0001087427,0.0005329474,0.002284889,0.1410837,0.07284107,0.0009311583,0.7362847,0.002443795],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9682284,0.000455213,0.0006574654,0.0001904182,0.0006709883,0.0004080939,0.02917318,0.0001286601,0.00008757025],"genre_scores_gemma":[0.9861621,0.00007512669,0.0004718077,0.0009438873,0.0001461797,0.0000502993,0.01206544,0.00003960694,0.00004552438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7321972,"threshold_uncertainty_score":0.999974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02505323453759762,"score_gpt":0.2727984575013813,"score_spread":0.2477452229637837,"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."}}