{"id":"W2891392316","doi":"10.1186/s40561-018-0065-y","title":"Static and dynamic eye movement metrics for students’ performance assessment","year":2018,"lang":"en","type":"article","venue":"Smart Learning Environments","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Eye tracking; Eye movement; Computer science; Tracking (education); Multimedia; Artificial intelligence; Psychology; Pedagogy","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":[0.000422966,0.0001362546,0.0001409493,0.0001268686,0.0002838244,0.00008005642,0.0004448054,0.00005035706,0.00000878782],"category_scores_gemma":[0.00003343357,0.0001305397,0.00002545981,0.0001429206,0.0001204528,0.0001529402,0.0003618039,0.0001713765,0.00004130784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001264707,"about_ca_system_score_gemma":0.00001191581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003165663,"about_ca_topic_score_gemma":0.000001279559,"domain_scores_codex":[0.9987668,0.0000454382,0.0001677214,0.0004010755,0.0003158369,0.0003031099],"domain_scores_gemma":[0.9994825,0.00006054216,0.0001079309,0.0002814721,0.00001179878,0.00005576192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000006907156,0.0002022756,0.8652236,0.00003117897,0.0000727469,0.00000263952,0.0002801498,0.0002087308,0.002356023,0.0007852278,0.000100195,0.1307303],"study_design_scores_gemma":[0.000557389,0.000733463,0.8939657,0.00001666441,0.00001280249,8.329127e-7,0.000038761,0.08930895,0.0004609457,0.0002904292,0.01445146,0.0001625527],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6290298,0.00001708776,0.3702348,0.0002267495,0.0001360523,0.0001597008,0.000001002584,0.00007654741,0.0001183739],"genre_scores_gemma":[0.9565952,0.00005399065,0.04142724,0.000193864,0.00001462518,0.00004992883,0.000004707904,0.00001292533,0.001647549],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3288075,"threshold_uncertainty_score":0.5323254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01039611268267233,"score_gpt":0.2963118811341161,"score_spread":0.2859157684514437,"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."}}