{"id":"W4412534168","doi":"10.1016/j.ecolind.2025.113886","title":"Urban flood susceptibility mapping using deep and machine learning algorithms as a management tool: A case study of Sanandaj City, Iran","year":2025,"lang":"en","type":"article","venue":"Ecological Indicators","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"University of Kurdistan","keywords":"Flood myth; Algorithm; Artificial intelligence; Computer science; Deep learning; Machine learning; Geography; Archaeology","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":[0.0005699133,0.0005603419,0.0003296457,0.00126212,0.0005566287,0.0005054662,0.0007942183,0.0005477048,0.000683376],"category_scores_gemma":[0.001150229,0.0001860112,0.0004534002,0.001437273,0.0005191824,0.0005383542,0.0005781777,0.0004401966,0.0001094637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001522748,"about_ca_system_score_gemma":0.0007978338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04904328,"about_ca_topic_score_gemma":0.08658857,"domain_scores_codex":[0.9997662,0.00007556927,0.00001196741,0.00003399337,0.00006204694,0.00005025758],"domain_scores_gemma":[0.9995199,0.0002145291,0.00006265706,0.0000389433,0.0001101056,0.00005382274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004113073,0.001116853,0.4275678,0.0002942953,0.0002588949,0.01529743,0.00295469,0.415536,0.004130284,0.00403567,0.009126656,0.1192701],"study_design_scores_gemma":[0.00005911815,0.0002169997,0.235653,0.00004767286,0.00009287782,0.0008468999,0.008119422,0.7448589,0.003218881,0.002688931,0.004125188,0.00007216018],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950891,0.00007432246,0.002765036,0.0002740136,0.000008069561,0.00003358484,0.0003702377,0.00006746838,0.001318284],"genre_scores_gemma":[0.9951192,0.00009591904,0.003813695,0.00001604713,0.000007293215,0.00001642664,0.0003269847,0.000009928747,0.0005945213],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04904328,"threshold_uncertainty_score":0.09751564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02752117113371531,"score_gpt":0.284991157147469,"score_spread":0.2574699860137537,"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."}}