{"id":"W2019617939","doi":"10.1145/1569901.1569908","title":"VISPLORE","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Visualization; Particle swarm optimization; Data visualization; Data exploration; Human–computer interaction; Range (aeronautics); Population; Interactive visual analysis; Interactive visualization; Artificial intelligence; Machine learning","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":[0.0009810097,0.001418829,0.001094621,0.00183687,0.0006788872,0.002585129,0.002564891,0.001223791,0.08154728],"category_scores_gemma":[0.00360405,0.0008139062,0.001518107,0.001373946,0.0004116477,0.002563129,0.002835763,0.002231536,0.02004277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005094114,"about_ca_system_score_gemma":0.000981602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00280944,"about_ca_topic_score_gemma":0.005148765,"domain_scores_codex":[0.9995235,0.0001080847,0.00002839628,0.0001029227,0.0001828887,0.00005427425],"domain_scores_gemma":[0.9986998,0.0007357206,0.000051816,0.0002243289,0.0002033375,0.00008501054],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009294272,0.0002270603,0.002201415,0.002011147,0.0002641256,0.0006168444,0.001007698,0.03335667,0.02132884,0.02911862,0.642646,0.2662922],"study_design_scores_gemma":[0.000424376,0.0001952512,0.003179968,0.0004046683,0.00008599903,0.0007350501,0.0002639397,0.2185551,0.02318834,0.04016642,0.7125547,0.0002462911],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.009829083,0.0008691197,0.5603013,0.0007251334,0.0003093798,0.0003439191,0.03661757,0.345106,0.0458985],"genre_scores_gemma":[0.125682,0.001924698,0.6427115,0.00127952,0.0001900562,0.002345565,0.08353934,0.08714303,0.05518423],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.08154728,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02198671893398045,"score_gpt":0.3068461844839032,"score_spread":0.2848594655499228,"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."}}