{"id":"W4391898411","doi":"10.31219/osf.io/3bxmg","title":"Struggles and Strategies in Understanding Information Visualizations","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Information visualization; Data science; Computer science; Epistemology; Visualization; Knowledge management; Philosophy; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0459877,0.001939893,0.00130381,0.006015487,0.005739295,0.02273248,0.00393137,0.006459771,0.003421166],"category_scores_gemma":[0.1641902,0.001857328,0.002047191,0.003856312,0.01247412,0.02707779,0.01230228,0.004794723,0.0006666706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003450722,"about_ca_system_score_gemma":0.002890948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003282772,"about_ca_topic_score_gemma":0.002466699,"domain_scores_codex":[0.9472262,0.03689524,0.002878767,0.004039005,0.006999704,0.001961062],"domain_scores_gemma":[0.8958369,0.08350066,0.005559288,0.005992773,0.006389795,0.002720601],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00007859292,0.00004536578,0.005229708,0.000482269,0.0000688262,0.001248845,0.9204801,0.0007644526,0.004179296,0.0385808,0.002179888,0.02666176],"study_design_scores_gemma":[0.00006444027,0.0001507017,0.005149721,0.001408173,0.000116453,0.002996969,0.7591328,0.01191712,0.00328102,0.1227733,0.09272395,0.0002852848],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7169012,0.005582407,0.223488,0.02086189,0.0003756816,0.0005005311,0.0002281055,0.001088046,0.03097406],"genre_scores_gemma":[0.9265391,0.001768966,0.06615802,0.0005523012,0.00007824504,0.0002858438,0.0002285148,0.0004814652,0.003907535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0459877,"threshold_uncertainty_score":0.2432091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05606406378030079,"score_gpt":0.3378593539241614,"score_spread":0.2817952901438607,"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."}}