{"id":"W2010997497","doi":"10.1145/2254556.2254653","title":"Hierarchically animated transitions in visualizations of tree structures","year":2012,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Animation; Computer science; Visualization; Tree (set theory); Computer animation; Computer graphics (images); Computer facial animation; Tree structure; Skeletal animation; Data visualization; Human–computer interaction; Artificial intelligence; Data structure; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001052285,0.00005546334,0.00008911883,0.0001716918,0.00003061118,0.00002826932,0.0002611782,0.00002890616,0.0001230211],"category_scores_gemma":[0.00002878153,0.00004816714,0.00002505855,0.0007205195,0.00003011424,0.0004373733,0.00004172119,0.00003808995,0.000007694898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007920892,"about_ca_system_score_gemma":0.00002829813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001026351,"about_ca_topic_score_gemma":0.00004921208,"domain_scores_codex":[0.9993813,0.00004400652,0.0002090593,0.00009222093,0.0001289046,0.0001445121],"domain_scores_gemma":[0.9996401,0.00002249087,0.00003395036,0.0001927906,0.00004401843,0.0000666235],"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":[6.895831e-7,0.00011055,0.002230438,0.000005979713,0.000004002701,2.80927e-7,0.0008026447,0.00007799772,0.001289398,0.9940159,0.000422673,0.001039483],"study_design_scores_gemma":[0.001414842,0.0001359758,0.2164944,0.00004790564,0.00002642087,0.00001831944,0.0005014539,0.7267883,0.01301053,0.03286332,0.008101964,0.0005966472],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007674008,0.00001967255,0.9850968,0.0004380295,0.00004918853,0.00005284405,0.00001243443,0.0000719639,0.006585062],"genre_scores_gemma":[0.9725288,0.000006277844,0.02701777,0.0002866714,0.00001216995,0.000001613192,0.00003499299,0.000003558658,0.0001081311],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9648548,"threshold_uncertainty_score":0.1964199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02396971189548477,"score_gpt":0.3186738947818161,"score_spread":0.2947041828863313,"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."}}