{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002298352,0.001439369,0.0008377347,0.001430812,0.0003500389,0.0004698914,0.0007027562,0.0007720293,0.007140436],"category_scores_gemma":[0.0008099171,0.0001949964,0.0006488848,0.001662016,0.0001379916,0.0002699796,0.0007561651,0.0006050876,0.008262685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002155253,"about_ca_system_score_gemma":0.0004089084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01256214,"about_ca_topic_score_gemma":0.03364072,"domain_scores_codex":[0.9998417,0.00001695903,0.00002176257,0.00004407418,0.00003790991,0.00003753777],"domain_scores_gemma":[0.9997013,0.00002590446,0.0000265796,0.00005682555,0.0001366376,0.00005269281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003079537,0.0007621643,0.04923785,0.002391852,0.0008821447,0.001970765,0.0003303574,0.00236757,0.03667677,0.0003132086,0.7487373,0.1532505],"study_design_scores_gemma":[0.001069954,0.0007704778,0.8195612,0.0004739943,0.000552576,0.003597845,0.0009391525,0.008624713,0.01289391,0.001475687,0.1497635,0.000276949],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1875588,0.002544514,0.004696259,0.0005658433,0.0008586594,0.000312912,0.7930545,0.004240961,0.006167679],"genre_scores_gemma":[0.1195142,0.0006473121,0.003459903,0.0001205355,0.0001947827,0.0003882526,0.8711854,0.0002190134,0.004270598],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01256214,"threshold_uncertainty_score":0.0249781,"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."}}