{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001198867,0.00003655466,0.00004608545,0.00004175501,0.00004107468,0.00008115265,0.0001932812,0.00001555052,0.00001175769],"category_scores_gemma":[0.00002185037,0.00003258872,0.0000231696,0.0001707118,0.00000822575,0.0002571697,0.00001406691,0.00001485775,0.00002690163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001027348,"about_ca_system_score_gemma":0.00004720517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003909142,"about_ca_topic_score_gemma":0.00001126066,"domain_scores_codex":[0.9996457,0.000009112963,0.00008110849,0.0001036259,0.00007561997,0.00008490661],"domain_scores_gemma":[0.9996797,0.00001514438,0.00001321994,0.0001312491,0.00008674268,0.00007393548],"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":[0.000002499897,0.000124129,0.00004371849,0.00001521637,0.00001517351,0.000001243821,0.00143018,0.001238877,0.0007991344,0.9460723,0.04729354,0.002964034],"study_design_scores_gemma":[0.0003590521,0.00005199498,0.00002645868,0.000003820217,0.00000440853,0.000002499072,0.0001331436,0.9441167,0.0006730229,0.002524762,0.05201747,0.00008667589],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003317603,0.00001297202,0.9945017,0.0006378392,0.00009017227,0.00005483206,0.000008209428,0.0001925244,0.004170068],"genre_scores_gemma":[0.7223874,0.000005297715,0.272089,0.002601435,0.00009406975,0.0000149685,0.00009627765,0.00001196787,0.002699606],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9435475,"threshold_uncertainty_score":0.1328929,"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."}}