{"id":"W4385079053","doi":"10.1145/3597465.3605226","title":"Visualizing a Tabular Data Repository to Facilitate Descriptive Tag Augmentation for New Tables","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Table (database); Computer science; Information retrieval; Inference; Data exploration; World Wide Web; Data mining; Data science; Visualization; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003489795,0.00009632755,0.0001074983,0.000158342,0.000156059,0.0003766552,0.0009740528,0.000024731,0.00001458411],"category_scores_gemma":[0.0001462522,0.00009188313,0.0000251109,0.0007892827,0.0000110012,0.001069336,0.0006151473,0.00002503276,0.0001604417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003552208,"about_ca_system_score_gemma":0.0001068818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002973517,"about_ca_topic_score_gemma":0.00007211936,"domain_scores_codex":[0.9988149,0.0000322456,0.0002316039,0.0004733016,0.0002236568,0.0002242492],"domain_scores_gemma":[0.9989101,0.00007332584,0.00005194887,0.0007355618,0.00008384015,0.0001452346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009453171,0.00003464091,0.0001477363,0.0000342795,0.00004164153,0.000008358688,0.003401304,0.0007597979,0.007965638,0.0803788,0.892913,0.01430527],"study_design_scores_gemma":[0.0003511445,0.00007705537,0.0001112823,0.00002488144,0.0000123957,0.0000014809,0.001192948,0.7123544,0.005275225,0.001287624,0.279111,0.0002005549],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006271263,0.00001808573,0.9969729,0.0008346802,0.0003094285,0.0002584928,0.0001056023,0.0003505366,0.0005231288],"genre_scores_gemma":[0.04143178,0.00008141833,0.7523445,0.006282783,0.0005296045,0.0001090575,0.005683802,0.00006969114,0.1934674],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7115946,"threshold_uncertainty_score":0.3746885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2215605382741364,"score_gpt":0.3715789612189416,"score_spread":0.1500184229448053,"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."}}