{"id":"W4414956415","doi":"10.1109/cmss66566.2025.11182335","title":"Comparative Machine Learning Framework for Rainfall Forecasting and Agricultural Loss Estimation","year":2025,"lang":"en","type":"article","venue":"","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Warning system; Estimation; Climate change; Random forest; Agriculture; Livelihood; Resilience (materials science); Food security","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":[0.000212539,0.0001107719,0.0001476764,0.00001771564,0.0003084096,0.00005085333,0.00007987592,0.00007118348,0.0001781304],"category_scores_gemma":[0.0004767284,0.00007640668,0.00003037517,0.0001833014,0.000130798,0.0001063555,0.0001282075,0.000167845,0.00002265815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005640578,"about_ca_system_score_gemma":0.00000251951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007388157,"about_ca_topic_score_gemma":0.00003894071,"domain_scores_codex":[0.9992874,0.00003664795,0.0001480182,0.0002386122,0.00008746779,0.0002019056],"domain_scores_gemma":[0.9993764,0.0004558123,0.00005807455,0.00005641857,0.000008546079,0.00004473494],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000101008,0.0001072283,0.0942284,0.00005747573,0.00005125316,0.00000358081,0.002378024,0.8294657,0.002183559,0.01941585,0.001640503,0.05036739],"study_design_scores_gemma":[0.0002210262,0.0001035947,0.01727762,0.00004362549,0.00001464547,0.0000071421,0.00004810937,0.9605864,0.0005110299,0.01979997,0.001256449,0.000130405],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8031347,0.00001901438,0.1847095,0.0006569643,0.00005114752,0.000231956,0.000001768561,0.00009281556,0.01110207],"genre_scores_gemma":[0.8605593,8.763101e-7,0.1380329,0.0002161383,0.00001187086,0.00001660329,0.00001144395,0.000003129865,0.001147719],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1311207,"threshold_uncertainty_score":0.3115774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03353127783090611,"score_gpt":0.2882462276345711,"score_spread":0.254714949803665,"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."}}