{"id":"W2527278991","doi":"10.1109/mcg.2016.90","title":"Sports Tournament Predictions Using Direct Manipulation","year":2016,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Tournament; Computer science; Interface (matter); Focus (optics); League; User interface; Visitor pattern; Human–computer interaction; Multimedia","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":[0.0007682757,0.001520729,0.0004826275,0.0005963992,0.0002924635,0.001250573,0.00137388,0.001131243,0.03432054],"category_scores_gemma":[0.006797648,0.0004063031,0.0005247504,0.0002552353,0.0002103848,0.001496613,0.002148018,0.0006392941,0.004861792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001528541,"about_ca_system_score_gemma":0.0002901105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001644252,"about_ca_topic_score_gemma":0.001938486,"domain_scores_codex":[0.9994305,0.0001171085,0.0000471348,0.0001504399,0.000213791,0.00004099683],"domain_scores_gemma":[0.9972817,0.001837127,0.0001119453,0.000336921,0.0003059111,0.000126398],"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":[0.005746723,0.001238727,0.0199929,0.001153999,0.0002350678,0.001296816,0.003697248,0.01015302,0.07522526,0.009685557,0.1493717,0.722203],"study_design_scores_gemma":[0.001610575,0.003347764,0.05100537,0.0007457697,0.0003409134,0.00206506,0.001331126,0.4684515,0.07499578,0.01669857,0.3786975,0.0007100308],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1543996,0.0005826075,0.6721914,0.0006809371,0.0006084176,0.001179641,0.006780664,0.1233054,0.04027137],"genre_scores_gemma":[0.6688951,0.0004104009,0.289994,0.0007176814,0.0001549913,0.001659976,0.006245224,0.003147126,0.02877545],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03432054,"threshold_uncertainty_score":0.1148136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03020593011352092,"score_gpt":0.2857579929975708,"score_spread":0.2555520628840499,"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."}}