{"id":"W2140704526","doi":"10.1109/iv.2007.139","title":"Visualizing Web Navigation Data with Polygon Graphs","year":2007,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Visualization; Polygon (computer graphics); Data visualization; Information visualization; Web application; Tree (set theory); Data structure; Data mining; Theoretical computer science; World Wide Web; 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":[0.0007246466,0.0007498351,0.0004262575,0.003323587,0.0005675864,0.002788629,0.0005017603,0.000555408,0.004182991],"category_scores_gemma":[0.004787734,0.0003492173,0.0006079203,0.002956351,0.0005072054,0.001868636,0.002116709,0.0008269921,0.000746805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000345291,"about_ca_system_score_gemma":0.0005454209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003432521,"about_ca_topic_score_gemma":0.003300758,"domain_scores_codex":[0.9993485,0.0002265484,0.00005467356,0.00007712068,0.0002542422,0.00003900798],"domain_scores_gemma":[0.9980618,0.001132471,0.0001740217,0.0001999422,0.0003346196,0.00009714963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001041982,0.0003155869,0.01562858,0.001429876,0.0002277729,0.001904407,0.01003289,0.2006657,0.05719185,0.1240859,0.04484265,0.5426327],"study_design_scores_gemma":[0.0001606284,0.0001538755,0.006757068,0.0002675531,0.0001005998,0.000971359,0.002310209,0.7131543,0.03647293,0.08725815,0.1521789,0.0002145405],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05841148,0.0005024167,0.9176662,0.00079357,0.0001023087,0.0001745358,0.003167591,0.01105486,0.008126942],"genre_scores_gemma":[0.3251866,0.001052221,0.6666048,0.0001209413,0.00006675015,0.0002402828,0.003160605,0.001317735,0.002250171],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004182991,"threshold_uncertainty_score":0.0139935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04017121575397124,"score_gpt":0.3430823389002629,"score_spread":0.3029111231462916,"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."}}