{"id":"W6888829327","doi":"10.2312/eurova.20231090","title":"ChatKG: Visualizing Temporal Patterns as Knowledge Graph","year":2023,"lang":"en","type":"article","venue":"TU/e Research Portal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Visualization; Knowledge graph; Graph; Temporal database; Data visualization; Oracle; Knowledge extraction; Information visualization","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002145081,0.000145436,0.0001756005,0.0008565246,0.0003416906,0.0004669281,0.001279443,0.00007216603,0.0003341775],"category_scores_gemma":[0.0002415931,0.0001369819,0.00009394257,0.00300287,0.0001101381,0.0006076983,0.001019777,0.0003155807,0.003663588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002432562,"about_ca_system_score_gemma":0.0002826349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001572468,"about_ca_topic_score_gemma":0.00009701801,"domain_scores_codex":[0.9970612,0.0002442244,0.0003046728,0.0005261757,0.001064784,0.0007989651],"domain_scores_gemma":[0.9984704,0.0001542903,0.00005532104,0.0007016252,0.000285092,0.0003332316],"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":[0.000009099966,0.0004532881,0.03863258,0.0001915025,0.000096399,0.001544412,0.003381223,0.0000173325,0.0007963356,0.6395864,0.2904637,0.02482765],"study_design_scores_gemma":[0.002481762,0.001199207,0.04142887,0.0005239241,0.00001973705,0.0001971545,0.005955872,0.382449,0.006788734,0.03445279,0.5223868,0.002116136],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5657349,0.0008210878,0.2088672,0.008115625,0.002969447,0.002002181,0.0002785979,0.00596207,0.2052489],"genre_scores_gemma":[0.9901515,0.0001853375,0.0002152107,0.000124041,0.0002115681,0.00002514534,0.0002265072,0.00002691892,0.008833815],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6051337,"threshold_uncertainty_score":0.9971122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1529981918903683,"score_gpt":0.4758466024575219,"score_spread":0.3228484105671536,"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."}}