{"id":"W4411117712","doi":"10.1016/j.ecohyd.2025.100674","title":"An analysis of rainfall variability and its association with agricultural productivity in the Brantas River Basin, Indonesia: Insights from a 26-year analysis","year":2025,"lang":"en","type":"article","venue":"Ecohydrology & Hydrobiology","topic":"Water resources management and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Pacific Institute for Climate Solutions","funders":"Universitas Negeri Malang","keywords":"Productivity; Agriculture; Structural basin; Geography; Association (psychology); Drainage basin; Water resource management; Environmental science; Hydrology (agriculture); Physical geography; Economics; Geology; Cartography; Economic growth; Psychology; Archaeology; Geomorphology","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":[],"consensus_categories":[],"category_scores_codex":[0.0004371915,0.0001595513,0.0005300308,0.0006576668,0.00005228525,0.00001617193,0.000189559,0.0002093846,0.00001837702],"category_scores_gemma":[0.00003202935,0.000106019,0.00008006965,0.002100698,0.00007135309,0.0001530573,0.00003831393,0.0001694204,0.000001522953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007111192,"about_ca_system_score_gemma":0.000005836005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002404516,"about_ca_topic_score_gemma":0.002247509,"domain_scores_codex":[0.9985138,0.0005824087,0.0002805251,0.0003643518,0.00006708082,0.0001918413],"domain_scores_gemma":[0.9993424,0.0002173681,0.0001138156,0.0002660269,0.00004143773,0.00001894247],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003337008,0.00006530043,0.5716951,0.000007865297,0.0027824,0.000001283422,0.001560666,0.4227666,0.0009157981,0.00015067,0.000006008022,0.00001491544],"study_design_scores_gemma":[0.000364278,0.00004982193,0.7694888,0.000001922438,0.002554686,2.208703e-7,0.00002687512,0.2269696,0.0002678169,0.0001472541,0.00003415261,0.00009463208],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980835,0.00005168758,0.0009581124,0.0002598541,0.00004724822,0.0002679462,0.00001978904,0.00006287848,0.0002490244],"genre_scores_gemma":[0.9994415,0.00001562784,0.0000931141,0.00005967664,0.00002064509,0.00002537006,0.0003248548,0.000006011835,0.00001321671],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1977936,"threshold_uncertainty_score":0.4323327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002486029227153944,"score_gpt":0.174281265609055,"score_spread":0.1717952363819011,"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."}}