{"id":"W2155068847","doi":"10.1145/1054972.1055079","title":"Improving revisitation in fisheye views with visit wear","year":2005,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Distortion (music); Representation (politics); Usability; Computer science; Space (punctuation); Object (grammar); Artificial intelligence; Computer vision; Human–computer interaction","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":[0.0011836,0.0008256453,0.0008144264,0.0006997348,0.0004107119,0.001626051,0.001216811,0.0008345824,0.002665794],"category_scores_gemma":[0.01601609,0.0005572681,0.0006605715,0.000748907,0.0006008441,0.002878135,0.002351998,0.00079661,0.0004509015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003798161,"about_ca_system_score_gemma":0.000510256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002335838,"about_ca_topic_score_gemma":0.003523191,"domain_scores_codex":[0.9989713,0.0002698931,0.0001017445,0.0001889885,0.0003678749,0.0001002255],"domain_scores_gemma":[0.9867742,0.007091874,0.001049263,0.003397209,0.001299374,0.0003881073],"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":[0.002525077,0.0004425542,0.01893724,0.001818352,0.0002431682,0.001020033,0.01216819,0.01733902,0.2220957,0.004277667,0.007767858,0.7113652],"study_design_scores_gemma":[0.0008014445,0.007365126,0.1615724,0.0008080532,0.0009753737,0.008272673,0.01198599,0.2117253,0.4629005,0.01531344,0.1171628,0.001116992],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5097497,0.002063585,0.476802,0.0003932141,0.0001086128,0.0002216568,0.0003485582,0.006138126,0.004174491],"genre_scores_gemma":[0.8129438,0.0007730078,0.1821156,0.0001088245,0.00004691045,0.000194375,0.0003584803,0.000437109,0.003021918],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002665794,"threshold_uncertainty_score":0.008917928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02070904530708233,"score_gpt":0.2891603967303329,"score_spread":0.2684513514232506,"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."}}