{"id":"W2182924104","doi":"10.1109/ldav.2015.7348082","title":"Skydive: An interactive data visualization engine","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Computer science; Visualization; Interactivity; Visual analytics; Data visualization; Interactive visual analysis; Information visualization; Analytics; Clutter; Data science; Information retrieval; Data mining; World Wide Web","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":[0.0002795391,0.00006701524,0.00006823947,0.00007802703,0.0000300391,0.000248447,0.001271223,0.00002176946,0.00004844007],"category_scores_gemma":[0.0001471233,0.00005765327,0.000007340703,0.0003500869,0.00001228224,0.003122218,0.0006591122,0.00003346719,0.0001619049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001908204,"about_ca_system_score_gemma":0.00006512238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002782719,"about_ca_topic_score_gemma":0.00001821027,"domain_scores_codex":[0.9992234,0.00005195574,0.0001263444,0.0002897058,0.0002082626,0.0001003888],"domain_scores_gemma":[0.998693,0.00001799955,0.00004456105,0.000938175,0.0001586308,0.0001476009],"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":[0.000006617907,0.0003720768,0.0007762445,0.000006135547,0.00002796815,0.00001060499,0.001932325,0.0003818135,0.00007724877,0.8391945,0.1190273,0.03818714],"study_design_scores_gemma":[0.0001838507,0.00004702702,0.00007715659,0.000003104752,0.000003081386,0.000003589326,0.0001507183,0.9436942,0.0003381963,0.0009246081,0.05448193,0.00009248729],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000292844,0.000007846174,0.9937559,0.0002401136,0.0002187765,0.00004144237,0.00001488085,0.0002270762,0.005201122],"genre_scores_gemma":[0.8477048,0.00001797257,0.1396915,0.004494726,0.0003073282,0.000003571902,0.003248344,0.00002550229,0.004506277],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9433124,"threshold_uncertainty_score":0.239578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1204784396990315,"score_gpt":0.4082524507496901,"score_spread":0.2877740110506586,"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."}}