{"id":"W3160036765","doi":"10.32473/flairs.v34i1.128474","title":"Confusion detection using cognitive ability tests","year":2021,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Confusion; Memorization; Cognition; Computer science; Support vector machine; Artificial intelligence; Cognitive psychology; Orientation (vector space); Psychology; Pattern recognition (psychology); Machine learning; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001462647,0.0002016066,0.0002238238,0.00009178733,0.0005810941,0.0004900055,0.00128028,0.0001367929,0.0002708333],"category_scores_gemma":[0.006148138,0.0001658744,0.0002806322,0.001003955,0.001004759,0.0005515,0.00109268,0.0008301278,0.00003349117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002487193,"about_ca_system_score_gemma":0.0003740937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001195499,"about_ca_topic_score_gemma":0.00002968973,"domain_scores_codex":[0.9964277,0.00009509473,0.0005708677,0.0007710458,0.001644272,0.0004910523],"domain_scores_gemma":[0.9939618,0.001129142,0.0002411019,0.0001768575,0.004375758,0.0001153051],"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":[0.00007054405,0.0001440157,0.000562349,0.00004847317,0.00002332785,0.000001534484,0.001626423,0.00004489794,0.9656116,0.02052252,0.00007923728,0.01126506],"study_design_scores_gemma":[0.0000449418,0.00006039767,0.0002638085,0.0002596281,0.00000876575,0.00002681557,0.004525518,0.06571788,0.8934524,0.03530254,0.0001899151,0.0001473938],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879504,0.00002339105,0.004309603,0.001848832,0.001171958,0.0003706221,0.00003480903,0.0000519427,0.004238419],"genre_scores_gemma":[0.9984805,0.00009098292,0.0005316973,0.000190284,0.0003549084,0.00002494513,0.000001390832,0.00001639066,0.0003089158],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07215922,"threshold_uncertainty_score":0.736034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2393936907274938,"score_gpt":0.4125526449569652,"score_spread":0.1731589542294714,"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."}}