{"id":"W2072589092","doi":"10.1111/j.1467-8659.2008.01233.x","title":"Interactive Exploratory Visualization of 2D Vector Fields","year":2008,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Glyph (data visualization); Computer science; Visualization; Computer graphics (images); Animation; Set (abstract data type); Field (mathematics); Computer animation; Euclidean vector; Vector field; Artificial intelligence; Computer vision; Mathematics","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":[0.0001104845,0.0001319435,0.0001855131,0.0002803776,0.0001251066,0.00005009086,0.0006578925,0.00007368603,0.0000100738],"category_scores_gemma":[0.00002102156,0.0001306385,0.00009792144,0.0007955267,0.00008677664,0.0007384922,0.0003443829,0.00009964535,0.00001700541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000135334,"about_ca_system_score_gemma":0.00006378445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006406841,"about_ca_topic_score_gemma":0.000007781761,"domain_scores_codex":[0.9988794,0.00006709711,0.0003065977,0.0002807131,0.0002702607,0.0001959012],"domain_scores_gemma":[0.9989604,0.00007306234,0.0001683829,0.0004722643,0.000244946,0.00008091686],"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":[0.000006486814,0.000223219,0.004921182,0.00002846828,0.00005459894,0.00001900601,0.002347007,0.0001333796,0.00006558048,0.9628703,0.0268654,0.002465346],"study_design_scores_gemma":[0.0006041531,0.0003468169,0.004068077,0.00007329578,0.00001156705,0.00003318617,0.00007193191,0.96663,0.004263489,0.006217835,0.01728308,0.0003965626],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006906149,0.00004775756,0.9917087,0.0002428426,0.0006533433,0.0000816055,0.000005908474,0.0001362653,0.0002174387],"genre_scores_gemma":[0.9921434,0.0001057172,0.006028823,0.001543728,0.00007539689,0.00000441394,0.00003764069,0.00001181022,0.00004905687],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9856799,"threshold_uncertainty_score":0.5327281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02946974761588329,"score_gpt":0.2877688119403164,"score_spread":0.2582990643244332,"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."}}