{"id":"W2908410696","doi":"10.29122/jstmc.v14i1.2680","title":"MENGULAS PENYEBAB BANJIR DI WILAYAH DKI JAKARTA DARI SUDUT PANDANG GEOLOGI, GEOMORFOLOGI DAN MORFOMETRI SUNGAI","year":2013,"lang":"id","type":"article","venue":"Jurnal Sains & Teknologi Modifikasi Cuaca","topic":"Multimedia Learning Systems","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Geography; Flood myth; Cartography; Forestry; Archaeology","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":[0.0004893836,0.0006068664,0.0004945773,0.001111289,0.002441423,0.007483286,0.0006378578,0.0007882986,0.03403245],"category_scores_gemma":[0.0007977103,0.0004100704,0.0003712805,0.00134003,0.001318154,0.001446593,0.002691011,0.001198104,0.007134326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002175712,"about_ca_system_score_gemma":0.003316023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0204949,"about_ca_topic_score_gemma":0.03927992,"domain_scores_codex":[0.9991797,0.0001112263,0.00005187215,0.0001904082,0.0002918982,0.0001748981],"domain_scores_gemma":[0.9990815,0.0001216395,0.000176798,0.0001102691,0.0002858726,0.0002240021],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001463943,0.000759965,0.2122494,0.003012374,0.0004405307,0.006346468,0.01874284,0.0008823723,0.1495018,0.05144691,0.02972365,0.52543],"study_design_scores_gemma":[0.00002118748,0.0002683499,0.1906661,0.0007194576,0.0001903345,0.003207554,0.01946841,0.0002569706,0.04667947,0.003569795,0.7348393,0.0001130402],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5630592,0.03623349,0.006363996,0.005702213,0.001056433,0.0001900842,0.004695212,0.0004647198,0.3822347],"genre_scores_gemma":[0.7469358,0.01656101,0.004440879,0.000681382,0.00009268068,0.0001002476,0.001524963,0.0001279015,0.2295351],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03403245,"threshold_uncertainty_score":0.1138499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02431599027969329,"score_gpt":0.2512308823036845,"score_spread":0.2269148920239912,"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."}}