{"id":"W2332159827","doi":"10.1177/154193120304700384","title":"Evaluating Interface Usability Based on Eye Movement and Hand Movement Behavioral Parameters","year":2003,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Usability; Eye movement; Computer science; Human–computer interaction; Fixation (population genetics); Task (project management); Action (physics); Interface (matter); User interface; Eye tracking; Movement (music); Cognition; Operator (biology); Artificial intelligence; Psychology; Engineering; Programming language","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":[0.004647666,0.0008223288,0.0007543302,0.001775059,0.0002304659,0.001080164,0.0003142018,0.0008142468,0.0011985],"category_scores_gemma":[0.0263222,0.0002184157,0.0004640429,0.0006361873,0.0003164969,0.001251679,0.000413885,0.0003781374,0.0003919613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002283281,"about_ca_system_score_gemma":0.0002121607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007056997,"about_ca_topic_score_gemma":0.0008161371,"domain_scores_codex":[0.9952579,0.002334386,0.0005088496,0.0002759103,0.001437649,0.0001852547],"domain_scores_gemma":[0.9688078,0.02149006,0.002385238,0.0008041937,0.005888729,0.000623972],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.007961041,0.002112293,0.3732015,0.001806836,0.0007998738,0.0003792306,0.003718798,0.002788751,0.3231467,0.0003955392,0.001189565,0.2824998],"study_design_scores_gemma":[0.0001635444,0.0110907,0.8982623,0.0001196554,0.0003748556,0.0007371216,0.00179081,0.01647755,0.06959265,0.0003150877,0.0009072896,0.0001684987],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9853185,0.0003087834,0.01214064,0.00004017906,0.00002007573,0.0001930619,0.0001084774,0.0001463436,0.001723953],"genre_scores_gemma":[0.9904174,0.0002172135,0.008268911,0.00003459225,0.00001953786,0.0001769176,0.000208478,0.00004074832,0.0006162791],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004647666,"threshold_uncertainty_score":0.02457952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05418818428542906,"score_gpt":0.366052542116389,"score_spread":0.31186435783096,"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."}}