{"id":"W2952507882","doi":"10.29122/alami.v3i1.3403","title":"PENGECEKAN DAN PERBAIKAN SECARA LANGSUNG FLOOD EARLY WARNING SYSTEM (FEWS) DI ALIRAN SUNGAI CIBONGAS, KABUPATEN BOGOR","year":2019,"lang":"id","type":"article","venue":"Jurnal Alami Jurnal Teknologi Reduksi Risiko Bencana","topic":"Multimedia Learning Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","funders":"Universitas Sam Ratulangi; Universitas Riau; London School of Economics and Political Science","keywords":"Physics; Humanities; Operating system; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004594274,0.000693059,0.0004244587,0.0006601608,0.0007905998,0.001691533,0.0003692926,0.0005830417,0.02995649],"category_scores_gemma":[0.0006851249,0.0002138419,0.0002697668,0.0005488843,0.0002451899,0.001255026,0.001102359,0.0007998949,0.009944373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004133228,"about_ca_system_score_gemma":0.0009332506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003132165,"about_ca_topic_score_gemma":0.004776041,"domain_scores_codex":[0.9996902,0.00004000192,0.00002042482,0.0000703777,0.0001276872,0.00005144],"domain_scores_gemma":[0.9993892,0.0001196349,0.00004798909,0.00009316058,0.0002448497,0.00010522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001490583,0.0002514274,0.02180305,0.0009108749,0.00007809274,0.001030542,0.001415817,0.002408154,0.1042121,0.004909057,0.1001029,0.7613873],"study_design_scores_gemma":[0.0001308286,0.0006364161,0.04047388,0.0003091637,0.0002302803,0.001603837,0.001668005,0.01451152,0.0762684,0.003247229,0.8607475,0.0001728916],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3375118,0.01125181,0.1061849,0.007162977,0.003153294,0.0007197247,0.009381253,0.04619775,0.4784364],"genre_scores_gemma":[0.6379498,0.005518853,0.02774283,0.0009746394,0.0004457624,0.0002836867,0.005589522,0.001367678,0.3201272],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02995649,"threshold_uncertainty_score":0.1002144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01391820709841098,"score_gpt":0.2336425392093686,"score_spread":0.2197243321109576,"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."}}