{"id":"W7043764702","doi":"","title":"Towards an improved understanding of the importance hydrologically diverse data for training flood forecasting models","year":2024,"lang":"en","type":"other","venue":"York University Digital Library (York University)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Flood myth; Flood forecasting; Equifinality; Exploit; Training (meteorology); Climate change; Notice; Flood warning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01126917,0.0008253759,0.0008857391,0.001351597,0.0005184255,0.003560536,0.00151731,0.001936865,0.001025742],"category_scores_gemma":[0.05447811,0.000799858,0.0008032225,0.001292031,0.001066495,0.006357438,0.00187591,0.005229796,0.0003931773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001315635,"about_ca_system_score_gemma":0.001620671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009740896,"about_ca_topic_score_gemma":0.006448444,"domain_scores_codex":[0.9979103,0.001102948,0.0001737071,0.0003099749,0.0004264233,0.00007663482],"domain_scores_gemma":[0.9732733,0.01969634,0.0009399669,0.002449707,0.003148373,0.0004921515],"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":[0.0001458022,0.0001921622,0.01525351,0.0004394759,0.0002168076,0.0001228905,0.0005277254,0.6858006,0.004312332,0.09264025,0.004774464,0.195574],"study_design_scores_gemma":[0.00001085989,0.00005186948,0.002669295,0.000168034,0.00003144927,0.00002116299,0.0001027544,0.9362534,0.001146382,0.05427808,0.005234901,0.00003176492],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05809989,0.005509735,0.9141524,0.01509695,0.0005507761,0.0001073296,0.0007810472,0.0003432715,0.005358533],"genre_scores_gemma":[0.5918358,0.009542789,0.3925596,0.001456671,0.001364704,0.0002064124,0.001359825,0.000150074,0.001524156],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01126917,"threshold_uncertainty_score":0.05959779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1575037388382519,"score_gpt":0.2213195581153088,"score_spread":0.06381581927705687,"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."}}