{"id":"W2340249237","doi":"10.1177/1473871615609787","title":"Eye tracking evaluation of visual analytics","year":2015,"lang":"en","type":"article","venue":"Information Visualization","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Visual analytics; Computer science; Eye tracking; Visualization; Cultural analytics; Analytics; Human–computer interaction; Tracking (education); Data science; Cognition; Field (mathematics); Process (computing); Data visualization; Artificial intelligence; Semantic analytics; Psychology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001392864,0.00007936778,0.0001081442,0.000353981,0.00004521228,0.00008939608,0.0002422625,0.00007975782,0.000006495486],"category_scores_gemma":[0.0005600179,0.00007945392,0.00002782514,0.0007503879,0.00003061018,0.0023442,0.00005379444,0.00005006052,0.00004720539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001032431,"about_ca_system_score_gemma":0.0001680977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009762013,"about_ca_topic_score_gemma":0.000001924219,"domain_scores_codex":[0.9985714,0.00009022321,0.0004123742,0.00009091066,0.0007214283,0.0001136546],"domain_scores_gemma":[0.9977828,0.00002032861,0.0003385587,0.0001955417,0.001617661,0.00004514493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001634765,0.0002266036,0.01951086,0.00006129997,0.00004872958,4.58228e-7,0.009405313,0.0510086,0.0006344166,0.4828029,0.001532342,0.4347521],"study_design_scores_gemma":[0.0005720312,0.00009299261,0.01370556,0.00001721778,0.00001862838,0.000001905056,0.0002983996,0.974771,0.006223449,0.003124138,0.001075315,0.00009932866],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1341014,0.00001587936,0.8631635,0.0001064187,0.0002002942,0.0001321568,9.71582e-7,0.0001955183,0.002083844],"genre_scores_gemma":[0.9969345,0.000001963594,0.002903999,0.00007680742,0.00001707978,0.000008093886,0.00004761522,0.000003133019,0.000006863935],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9237624,"threshold_uncertainty_score":0.3240037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06827886543160647,"score_gpt":0.3785115235552849,"score_spread":0.3102326581236784,"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."}}