{"id":"W4389903588","doi":"10.1016/j.dib.2023.109981","title":"Loosely controlled experimental EEG datasets for higher-order cognitions in design and creativity tasks","year":2023,"lang":"en","type":"article","venue":"Data in Brief","topic":"Design Education and Practice","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Creativity; Electroencephalography; Task (project management); Computer science; Cognition; Artificial intelligence; Sketch; Brain–computer interface; Cognitive psychology; Channel (broadcasting); Psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008531884,0.0008010051,0.0004653727,0.0008419253,0.0003472457,0.0005723583,0.0005909503,0.0008744047,0.004154269],"category_scores_gemma":[0.006532168,0.0001794688,0.0006281718,0.0009667156,0.0006593349,0.0004654792,0.001020245,0.0008729575,0.001061919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002836088,"about_ca_system_score_gemma":0.0002847079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006449439,"about_ca_topic_score_gemma":0.001605237,"domain_scores_codex":[0.9987503,0.0003605527,0.0001454224,0.0003854796,0.0002662521,0.0000920571],"domain_scores_gemma":[0.9961448,0.001486628,0.000454332,0.0009405973,0.0007332127,0.0002404674],"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":[0.01001821,0.007959315,0.07921391,0.006738583,0.001349082,0.002305368,0.004572656,0.02326245,0.4098018,0.005470382,0.04478587,0.4045224],"study_design_scores_gemma":[0.002077697,0.005948628,0.8394185,0.000393179,0.0003932979,0.003618727,0.001574545,0.02355946,0.05898939,0.01224172,0.05137789,0.0004068108],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.8714108,0.001133214,0.0803,0.0003707041,0.0002990931,0.003379158,0.03420235,0.0009764536,0.007928093],"genre_scores_gemma":[0.8569952,0.0005527353,0.06521634,0.0003456753,0.0001928357,0.01248497,0.06114976,0.0001875105,0.002874977],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.004154269,"threshold_uncertainty_score":0.01389742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09887854378390319,"score_gpt":0.359751617984316,"score_spread":0.2608730742004128,"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."}}