{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001199662,0.000514043,0.0003985912,0.001069769,0.0002426339,0.0008948739,0.0003898823,0.0004593162,0.001424851],"category_scores_gemma":[0.008140756,0.0002029411,0.0002174036,0.0003803294,0.0002343174,0.0007356079,0.0009220075,0.0003782923,0.0003218603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002073658,"about_ca_system_score_gemma":0.0001987779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001523447,"about_ca_topic_score_gemma":0.002247434,"domain_scores_codex":[0.9990182,0.000323869,0.00009221008,0.000212039,0.0002541921,0.00009962361],"domain_scores_gemma":[0.996588,0.00148075,0.0007404349,0.0002773571,0.0006302435,0.0002832913],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00177566,0.0005951728,0.581569,0.0004838444,0.0002979418,0.0004464688,0.009154412,0.001665444,0.2512515,0.000545226,0.001574074,0.1506413],"study_design_scores_gemma":[0.00004341561,0.001454274,0.9633684,0.00004046414,0.000114698,0.0005295418,0.001526785,0.00997554,0.0212125,0.0004506032,0.00119889,0.00008502586],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9746436,0.00010856,0.02335573,0.00003291633,0.00001278545,0.0001221569,0.0002277968,0.0002028925,0.001293464],"genre_scores_gemma":[0.9887099,0.00007640949,0.01010142,0.00004248391,0.00001029148,0.0001447069,0.0001951753,0.00003828917,0.0006814999],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001523447,"threshold_uncertainty_score":0.006344497,"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."}}