{"id":"W4282969634","doi":"10.21606/drs.2022.257","title":"Data-painting: Expressive free-form visualisation","year":2022,"lang":"en","type":"article","venue":"Proceedings of DRS","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; European Commission; Alberta Innovates - Technology Futures","keywords":"Visualization; Computer science; Representation (politics); Data visualization; Expressive power; Human–computer interaction; Expressivity; Information visualization; Painting; External Data Representation; Data science; Artificial intelligence; Theoretical computer science; Visual arts","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":[0.0005446743,0.00007730936,0.0001108009,0.0001325449,0.0001775726,0.0001290768,0.00246893,0.000016518,0.00006275957],"category_scores_gemma":[0.0002585734,0.00008093271,0.00002446729,0.000518946,0.00002832382,0.001270407,0.002635369,0.00008926065,0.000004765483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002811253,"about_ca_system_score_gemma":0.00003862291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009618755,"about_ca_topic_score_gemma":4.41884e-7,"domain_scores_codex":[0.9988404,0.000005651574,0.0002388822,0.0003069862,0.0004610679,0.0001470388],"domain_scores_gemma":[0.9991614,0.00002565816,0.0002698872,0.0003263623,0.000167989,0.0000486676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000907378,0.0002629138,0.003359077,0.0001120057,0.00004155963,0.000001742238,0.004526022,0.00004330188,0.009897384,0.7877907,0.1840233,0.009932932],"study_design_scores_gemma":[0.001138478,0.0003027391,0.0008780232,0.00004875151,0.00004009518,0.00002288299,0.00602864,0.6553882,0.02241599,0.02754273,0.2855971,0.0005963449],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4420751,0.0003924297,0.4422018,0.01070534,0.002192242,0.001684107,0.001737809,0.002158846,0.09685235],"genre_scores_gemma":[0.9806649,0.00001239269,0.0178879,0.0006004528,0.00008248414,0.00001887372,0.0001642015,0.00001464403,0.0005541636],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7602479,"threshold_uncertainty_score":0.4587927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04447041341731357,"score_gpt":0.3051562584466951,"score_spread":0.2606858450293816,"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."}}