{"id":"W2557517892","doi":"10.21609/jsi.v12i2.481","title":"VISUALISASI DATA INTERAKTIF DATA TERBUKA PEMERINTAH PROVINSI DKI JAKARTA: TOPIK EKONOMI DAN KEUANGAN DAERAH","year":2016,"lang":"en","type":"article","venue":"Jurnal Sistem Informasi","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Visualization; Computer science; Data science; Data visualization; Quarter (Canadian coin); World Wide Web; Data mining; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002323379,0.0008349388,0.000499195,0.006461123,0.001120474,0.007106838,0.0006268698,0.0005382418,0.02906988],"category_scores_gemma":[0.0064726,0.0005026411,0.0005566138,0.01091829,0.0007560707,0.004898486,0.002489236,0.001238626,0.008610764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00126708,"about_ca_system_score_gemma":0.002446844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01132364,"about_ca_topic_score_gemma":0.01391599,"domain_scores_codex":[0.9985754,0.0003860676,0.0001500727,0.0002420816,0.0005499083,0.00009629708],"domain_scores_gemma":[0.9952955,0.00204444,0.0004138344,0.0007279837,0.001212565,0.0003056972],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008621404,0.0002864357,0.05419807,0.003759589,0.0002836105,0.00150289,0.0104721,0.006121843,0.009529265,0.03934274,0.3961103,0.477531],"study_design_scores_gemma":[0.00005096581,0.00006464721,0.063898,0.001246099,0.0001308343,0.001100088,0.01095464,0.01064759,0.009111074,0.01694288,0.8856654,0.0001877838],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1982966,0.01309998,0.1491724,0.02310079,0.003101522,0.0008877823,0.3001487,0.03712362,0.2750687],"genre_scores_gemma":[0.6189945,0.01353918,0.1455976,0.001096801,0.0005533723,0.0007200859,0.1382912,0.005489088,0.07571825],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02906988,"threshold_uncertainty_score":0.09724844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06894903330201307,"score_gpt":0.3238826768715423,"score_spread":0.2549336435695292,"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."}}