{"id":"W2752511750","doi":"10.1145/3102071.3102089","title":"Vixen","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; USable; Visualization; Data visualization; Human–computer interaction; Process (computing); Focus (optics); Domain (mathematical analysis); Representation (politics); Data science; External Data Representation; Multimedia; Data mining; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0000430512,0.00001709472,0.00002034109,0.000009447194,0.0001414919,0.0004418225,0.0007973218,0.000006414118,0.00005761189],"category_scores_gemma":[0.00002379368,0.00001340297,0.000008534295,0.00001318159,0.00001148313,0.0003981646,0.0001760028,0.000009361745,0.0003117493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001595752,"about_ca_system_score_gemma":0.000007440434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001154434,"about_ca_topic_score_gemma":0.000003504359,"domain_scores_codex":[0.9998103,0.000002382968,0.00002936026,0.00006382669,0.00005090965,0.00004326845],"domain_scores_gemma":[0.9993928,0.000002808916,0.00002058573,0.0005457891,0.00001416155,0.00002381996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[3.995212e-8,0.000006244524,0.0008487846,4.904865e-7,0.000001215018,0.000001377433,0.00001722842,0.000001413975,0.0000145567,0.9632044,0.0272004,0.008703865],"study_design_scores_gemma":[0.0001590256,0.00001109423,0.01264094,0.000002948467,0.000001076761,0.000002092672,0.000005543147,0.2880112,0.001567367,0.009849646,0.6876453,0.0001037922],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00006435298,0.000001207888,0.8621941,0.002241315,0.00006468713,0.000006984772,1.906489e-7,0.00004862524,0.1353785],"genre_scores_gemma":[0.9301869,0.000007394393,0.03443578,0.00365504,0.00004671657,5.640511e-7,0.000001734921,0.000002175841,0.03166369],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9533547,"threshold_uncertainty_score":0.4260504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04377433604875836,"score_gpt":0.3480795268858432,"score_spread":0.3043051908370848,"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."}}