{"id":"W2141752259","doi":"10.1145/2702123.2702476","title":"Trajectory Bundling for Animated Transitions","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Defense Advanced Research Projects Agency","keywords":"Computer science; Tracking (education); Trajectory; Movement (music); Computer vision; Video tracking; Object (grammar); Visualization; Artificial intelligence; Animation; Computer graphics (images); Human–computer interaction","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":[0.001095894,0.0007698506,0.0004830117,0.0007842899,0.0005603181,0.001329307,0.000925541,0.0008618946,0.007393465],"category_scores_gemma":[0.006744916,0.0005406677,0.0006938501,0.0005469426,0.0006329025,0.001881806,0.002407858,0.001012175,0.001034029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003915126,"about_ca_system_score_gemma":0.0004244256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000635036,"about_ca_topic_score_gemma":0.001032564,"domain_scores_codex":[0.9993597,0.0002068133,0.00005300739,0.000157436,0.0001666057,0.00005652367],"domain_scores_gemma":[0.9969807,0.001454426,0.0002960338,0.0007029477,0.0003102117,0.0002556399],"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":[0.001577071,0.0004810798,0.003448336,0.001029981,0.000128536,0.0009208109,0.004247157,0.09413742,0.354169,0.05834893,0.01216483,0.4693469],"study_design_scores_gemma":[0.0002439972,0.0007490257,0.002886296,0.0001805066,0.00009848062,0.001070367,0.0004477554,0.7699831,0.1049499,0.02945017,0.08979058,0.0001498643],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03548987,0.0001793568,0.9574514,0.0001493777,0.00008168945,0.0001389344,0.0001402583,0.004169453,0.002199582],"genre_scores_gemma":[0.2488832,0.000222177,0.7462339,0.0001150961,0.00003623088,0.0003854166,0.0003675903,0.001303475,0.002452906],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007393465,"threshold_uncertainty_score":0.02473366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08512820427975884,"score_gpt":0.3340681487253276,"score_spread":0.2489399444455687,"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."}}