{"id":"W4377014401","doi":"10.1145/3591137","title":"Unconscious Frustration: Dynamically Assessing User Experience using Eye and Mouse Tracking","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"BitTorrent tracker; Eye tracking; Computer science; Task (project management); Computer mouse; Human–computer interaction; Point (geometry); Eye movement; Computer vision; Unconscious mind; Artificial intelligence; Tracking (education); Cursor (databases); Psychology; Engineering","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":[0.0002538785,0.000187859,0.0001984196,0.0002780083,0.0003942646,0.0005430164,0.001516777,0.0001007856,0.000002276599],"category_scores_gemma":[0.0001712996,0.0001534576,0.00007613406,0.0005310178,0.0001319053,0.001363116,0.0009211392,0.0003398894,0.000005766174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009313773,"about_ca_system_score_gemma":0.00001665534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001833849,"about_ca_topic_score_gemma":0.000002905244,"domain_scores_codex":[0.9986069,0.00001626459,0.0003376325,0.0004965333,0.0002853318,0.000257363],"domain_scores_gemma":[0.99887,0.0000911521,0.0003479577,0.0004265482,0.0002226635,0.0000416673],"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":[0.00002603673,0.0002495334,0.05610158,0.0001544532,0.00008430708,0.000009264877,0.004877492,0.0007541871,0.8244028,0.02959049,0.001046173,0.08270366],"study_design_scores_gemma":[0.0008848942,0.0004189689,0.2889906,0.001024585,0.00004383022,0.0001215872,0.001375893,0.3432091,0.3456636,0.01688585,0.0005367409,0.0008442398],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878275,0.000004662784,0.009714694,0.001211553,0.0005437207,0.0001371741,6.244666e-7,0.0004374229,0.0001226569],"genre_scores_gemma":[0.9779546,0.000002606431,0.02171095,0.0001154235,0.0001061028,0.000009727942,6.884304e-7,0.00001516292,0.00008478706],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4787392,"threshold_uncertainty_score":0.6257821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08054506340083589,"score_gpt":0.365363218046566,"score_spread":0.2848181546457301,"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."}}