{"id":"W4402721926","doi":"10.1145/3670947.3670977","title":"Investigating User Estimation of Missing Data in Visual Analysis","year":2024,"lang":"en","type":"article","venue":"Graphics Interface","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Universitas Brawijaya","keywords":"Computer science; Estimation; Missing data; Artificial intelligence; Data mining; Machine learning; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006220104,0.00008322208,0.0001530285,0.0007014247,0.00002983394,0.0002895853,0.0008497279,0.00004091562,0.000009954754],"category_scores_gemma":[0.0002116361,0.00008103203,0.00004179237,0.003764493,0.00005702157,0.0008820691,0.0004619456,0.0001277513,0.000007161041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001437022,"about_ca_system_score_gemma":0.00005801287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000084817,"about_ca_topic_score_gemma":0.00006297684,"domain_scores_codex":[0.9989144,0.00006198413,0.0003322766,0.000346201,0.000230614,0.0001145411],"domain_scores_gemma":[0.9991146,0.000120118,0.00007200217,0.0006086651,0.00004131098,0.00004327913],"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":[0.000003121761,0.0002491851,0.02309811,0.0006616557,0.0009139031,0.00003732087,0.005810338,0.08481739,0.002282768,0.7593393,0.003638917,0.119148],"study_design_scores_gemma":[0.0000393266,0.00001081403,0.0007222139,0.0001391977,0.00004947024,0.000001428814,0.00003360815,0.9927743,0.001251593,0.004440105,0.0004555327,0.00008239536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02563033,0.0002477222,0.9733136,0.0004659231,0.0001071721,0.00003411692,0.00001846109,0.00008034885,0.0001023758],"genre_scores_gemma":[0.9654915,0.0000158666,0.0342546,0.0001118399,0.000008371158,6.031742e-7,0.00008285241,0.000005714264,0.00002859182],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9398612,"threshold_uncertainty_score":0.330439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06049592183069265,"score_gpt":0.3864893038071454,"score_spread":0.3259933819764528,"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."}}