{"id":"W2547332248","doi":"10.1109/gem.2014.7048085","title":"iMind: An alternative dialogue between viewers and artists","year":2014,"lang":"en","type":"article","venue":"","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Entertainment; The arts; Computer science; Multimedia; Interface (matter); Media arts; Human–computer interaction; Brain–computer interface; Interactive art; Visual arts; Art; 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":[0.002205494,0.0006840452,0.0003425845,0.0006185813,0.001035907,0.003475728,0.001421184,0.00156668,0.01943064],"category_scores_gemma":[0.005561055,0.0002457403,0.0004200559,0.0002148843,0.001369385,0.00345046,0.00503426,0.001458698,0.002240979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000292113,"about_ca_system_score_gemma":0.0002567946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001192874,"about_ca_topic_score_gemma":0.0003424976,"domain_scores_codex":[0.9989815,0.0005650473,0.00002780671,0.000154185,0.0001693596,0.0001020684],"domain_scores_gemma":[0.9974555,0.001806962,0.0000771964,0.0002348199,0.0001147441,0.0003107744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003534918,0.0008518121,0.00545113,0.002069843,0.000093737,0.004991689,0.1775748,0.00236524,0.1903911,0.1155628,0.05172354,0.4453895],"study_design_scores_gemma":[0.0004035422,0.001592233,0.004852397,0.0005779862,0.000110463,0.004623725,0.04407976,0.01601998,0.04012749,0.03122256,0.8561426,0.000247334],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3521661,0.001584708,0.3819112,0.005259854,0.001301162,0.0007538062,0.0005717432,0.005510109,0.2509413],"genre_scores_gemma":[0.7726321,0.0004804067,0.1592184,0.001562567,0.0004309814,0.0006549595,0.0004422664,0.001368815,0.06320954],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01943064,"threshold_uncertainty_score":0.06500196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04292842695844278,"score_gpt":0.297493538093377,"score_spread":0.2545651111349342,"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."}}