{"id":"W6907160317","doi":"10.20380/gi2022.13","title":"I'm Not Sure: Designing for Ambiguity in Visual Analytics","year":2022,"lang":"en","type":"article","venue":"Canada Human-Computer Communications Society","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Sensemaking; Visual analytics; Ambiguity; Relevance (law); Visualization; Cultural analytics; Analytics; Meaning (existential)","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":[0.03144979,0.00160819,0.0007403892,0.00240024,0.003938558,0.01347056,0.002542967,0.002870001,0.004052644],"category_scores_gemma":[0.1041017,0.001270205,0.001229101,0.001509114,0.01103944,0.01806141,0.009620972,0.004000804,0.001002965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002070783,"about_ca_system_score_gemma":0.003388255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001479572,"about_ca_topic_score_gemma":0.001580515,"domain_scores_codex":[0.9740936,0.02005075,0.001011918,0.001765539,0.002343923,0.0007342573],"domain_scores_gemma":[0.9369234,0.04396981,0.003977187,0.008707227,0.004716199,0.001706163],"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":[0.0005419445,0.0002286302,0.009319464,0.001467012,0.0001632915,0.00121851,0.2179409,0.01639771,0.01852689,0.4589147,0.01363196,0.261649],"study_design_scores_gemma":[0.0001529533,0.0002372803,0.001781126,0.00104479,0.0001783482,0.0009810377,0.03816252,0.06595024,0.01204217,0.7818373,0.09738073,0.0002514444],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03096119,0.0004659639,0.9461794,0.008312141,0.0001875117,0.000316434,0.0000591944,0.001188958,0.01232922],"genre_scores_gemma":[0.4218533,0.0003776888,0.5735973,0.0009313895,0.00007664824,0.0005837668,0.0001036585,0.0005035829,0.001972735],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03144979,"threshold_uncertainty_score":0.1663244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07209690797647186,"score_gpt":0.3328927987694109,"score_spread":0.2607958907929391,"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."}}