{"id":"W7115184623","doi":"10.3390/w17243551","title":"Prophet-Based Artificial Intelligence Versus Seasonal Auto-Regressive Models for Flood Forecasting with Exogenous Variables","year":2025,"lang":"en","type":"article","venue":"Water","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mean squared error; Flood myth; Seasonality; Flood forecasting; Mean square; Flood risk management; Estimation; Forecast skill","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001202242,0.0005765406,0.0004822081,0.0004399641,0.0001942467,0.0007544456,0.0007031725,0.0004094974,0.001038034],"category_scores_gemma":[0.002642354,0.0002087316,0.0004261906,0.0005343841,0.0003726457,0.0008150766,0.0005132077,0.0009526091,0.0002411438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004106493,"about_ca_system_score_gemma":0.0006771649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004770728,"about_ca_topic_score_gemma":0.00564102,"domain_scores_codex":[0.9997187,0.0001096507,0.00002176665,0.00006210726,0.00007060573,0.0000171235],"domain_scores_gemma":[0.9989406,0.0007580523,0.0001013926,0.00007341082,0.0001088081,0.00001768003],"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":[0.0001157311,0.00003297885,0.001726156,0.00007481757,0.00008429239,0.00004472719,0.00004270969,0.9262028,0.001468495,0.007428481,0.0004525255,0.06232625],"study_design_scores_gemma":[0.000002828951,0.00003678642,0.0002600042,0.000004685882,0.000005555703,0.00001167689,0.000005254439,0.9976278,0.0002353505,0.001561967,0.00024424,0.000003838463],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1735839,0.001581652,0.812524,0.0006568087,0.0001618049,0.00008187029,0.0002000689,0.0007801437,0.01042974],"genre_scores_gemma":[0.9041684,0.0006570494,0.09129617,0.0001371163,0.00006848793,0.00007109857,0.0002599287,0.00004798247,0.003293771],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004770728,"threshold_uncertainty_score":0.0094859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0599380690575475,"score_gpt":0.2554228780041284,"score_spread":0.1954848089465809,"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."}}