{"id":"W3120337415","doi":"10.48550/arxiv.2101.02768","title":"EmoconLite: Bridging the Gap Between Emotiv and Play for Children With Severe Disabilities","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Headset; Brain–computer interface; Software deployment; Bridging (networking); Computer science; Software; Headphones; Human–computer interaction; CLIPS; Multimedia; Electroencephalography; Computer security; Artificial intelligence; Engineering; Psychology; Software engineering; Telecommunications; Operating system","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":[0.0007873399,0.0007019255,0.0003195446,0.0006883784,0.000433278,0.0008404247,0.0009132404,0.0007795246,0.008880937],"category_scores_gemma":[0.003508321,0.0002082914,0.0004902203,0.0003287958,0.0005653541,0.00109339,0.003017622,0.0009777704,0.001815177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006139071,"about_ca_system_score_gemma":0.001481932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003266901,"about_ca_topic_score_gemma":0.008407121,"domain_scores_codex":[0.9991798,0.0001818606,0.00007020044,0.0001049038,0.0003194375,0.0001438015],"domain_scores_gemma":[0.9991184,0.0003009888,0.00008517125,0.00006013293,0.0001518362,0.0002834156],"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":[0.0005733657,0.0004939518,0.0085325,0.000954497,0.00004779736,0.00129787,0.001804447,0.0002760814,0.01351534,0.003455741,0.05282938,0.916219],"study_design_scores_gemma":[0.0004927993,0.001711477,0.1142028,0.002953186,0.0002566055,0.0127466,0.002152658,0.006755408,0.03255543,0.005869102,0.8200386,0.0002653364],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5482085,0.02008954,0.205482,0.01829937,0.001314914,0.001914588,0.005704449,0.03583392,0.1631527],"genre_scores_gemma":[0.6913152,0.01345672,0.2396695,0.007546029,0.00040494,0.003105397,0.004210784,0.00311082,0.03718067],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008880937,"threshold_uncertainty_score":0.0297097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0795366257679758,"score_gpt":0.2112392383498049,"score_spread":0.1317026125818291,"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."}}