{"id":"W4391479181","doi":"10.24912/jmts.v7i1.26048","title":"ANALISIS PERBANDINGAN DEBIT PADA DAS CIMANUK-COPONG KABUPATEN GARUT AKIBAT PERUBAHAN TATA GUNA LAHAN","year":2024,"lang":"en","type":"article","venue":"JMTS Jurnal Mitra Teknik Sipil","topic":"Economic Growth and Fiscal Policies","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","funders":"","keywords":"Biology","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":[0.0007353773,0.0004914519,0.0003149792,0.001933359,0.0009405194,0.001339211,0.0004868395,0.0002996363,0.009687786],"category_scores_gemma":[0.001503262,0.0002041566,0.0003418848,0.003480677,0.0004853637,0.0006135403,0.0008038679,0.0004514096,0.001505531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001182786,"about_ca_system_score_gemma":0.00137142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03414903,"about_ca_topic_score_gemma":0.06045494,"domain_scores_codex":[0.9994534,0.0000898279,0.00004410187,0.0001059453,0.0002096454,0.00009703194],"domain_scores_gemma":[0.9990996,0.0001725242,0.00009533018,0.00006333244,0.0005066737,0.00006256111],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002870488,0.0001989323,0.6807418,0.001139273,0.0003443561,0.003715185,0.02205786,0.002778265,0.02508401,0.006779247,0.01223872,0.2446354],"study_design_scores_gemma":[0.000006422096,0.0001040111,0.8586994,0.0001583601,0.0001280413,0.0009546254,0.02894885,0.002418128,0.006396824,0.0004788357,0.1016659,0.00004061302],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9593965,0.0013099,0.002035575,0.0003330602,0.00005167052,0.0001366166,0.002604388,0.0000821308,0.03405013],"genre_scores_gemma":[0.975222,0.001087069,0.003242705,0.0001159789,0.0000160844,0.0001661594,0.002910149,0.00004618904,0.01719373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03414903,"threshold_uncertainty_score":0.06790048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03101717322411761,"score_gpt":0.2473256120947983,"score_spread":0.2163084388706806,"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."}}