{"id":"W4391093312","doi":"10.1109/bigdata59044.2023.10386099","title":"Visual Insight Recommendation: From Ranking Insight Visualizations to Insight Types","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Computer science; Visualization; Ranking (information retrieval); Categorical variable; Focus (optics); Variety (cybernetics); Recommender system; Visual analytics; Information retrieval; Rank (graph theory); Data visualization; Class (philosophy); Learning to rank; Human–computer interaction; Information visualization; Data science; Data mining; Machine learning; Artificial intelligence","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":[0.002655171,0.002315832,0.001103029,0.006387322,0.000717123,0.003797378,0.001676275,0.001295923,0.012584],"category_scores_gemma":[0.02382853,0.001038767,0.001176472,0.003921559,0.0004527796,0.006355191,0.002544353,0.002188931,0.005084563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007763641,"about_ca_system_score_gemma":0.0009551557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006156093,"about_ca_topic_score_gemma":0.01371121,"domain_scores_codex":[0.9984738,0.0003658989,0.0001558515,0.0004203464,0.0004805979,0.0001034252],"domain_scores_gemma":[0.9895253,0.004542306,0.0009355863,0.002152697,0.002207843,0.0006363002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001690606,0.0004771732,0.0160437,0.00152869,0.0002996249,0.0002791719,0.002063636,0.007140747,0.01629639,0.009804226,0.1212227,0.8231533],"study_design_scores_gemma":[0.0008506286,0.001597075,0.02749885,0.001233794,0.0005248456,0.001182366,0.002887334,0.600437,0.0502059,0.09257099,0.2202866,0.000724617],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05230568,0.002710436,0.7192977,0.002327829,0.0003909163,0.001045786,0.01953907,0.1920985,0.01028404],"genre_scores_gemma":[0.1548943,0.001193681,0.8174802,0.0004904934,0.0001540858,0.0005766102,0.01569795,0.003769384,0.005743323],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.012584,"threshold_uncertainty_score":0.04209769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04002837939470994,"score_gpt":0.3355294241055158,"score_spread":0.2955010447108058,"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."}}