{"id":"W4413126136","doi":"10.5194/egusphere-2025-3146","title":"Rapid Flood Mapping from Aerial Imagery Using Fine-Tuned SAM and ResNet-Backboned U-Net","year":2025,"lang":"en","type":"article","venue":"","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Innovation Cluster (Canada)","funders":"Deutsche Forschungsgemeinschaft","keywords":"Aerial imagery; Flood myth; Residual neural network; Remote sensing; Aerial photos; Environmental science; Cartography; Geography; Computer science; Artificial intelligence; Deep learning; 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":[0.000927176,0.002062074,0.0007213256,0.00180012,0.0003981802,0.000685058,0.001600236,0.001199911,0.001890348],"category_scores_gemma":[0.001914821,0.0005149856,0.0008349626,0.0007692845,0.0004357571,0.001556026,0.000714764,0.001155096,0.001016043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001113501,"about_ca_system_score_gemma":0.0008682573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01742043,"about_ca_topic_score_gemma":0.02196977,"domain_scores_codex":[0.9997132,0.00004779402,0.0000148792,0.0001238644,0.00004283742,0.0000574272],"domain_scores_gemma":[0.9995291,0.0001634805,0.0000558905,0.00007830308,0.0001272284,0.00004600045],"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":[0.00111755,0.0005042981,0.007283634,0.0003129172,0.0002808201,0.0005103008,0.0002162682,0.6223236,0.01886679,0.001195987,0.02033157,0.3270563],"study_design_scores_gemma":[0.00001640674,0.00004888171,0.0007965761,0.00001050584,0.00001682522,0.00002924505,0.00003190801,0.9938585,0.00402329,0.000538606,0.0006196306,0.000009650105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6824593,0.002456183,0.2414163,0.001414532,0.001036548,0.0005422801,0.00531349,0.05665266,0.008708751],"genre_scores_gemma":[0.8870934,0.0002867045,0.1029533,0.0003390334,0.00008822908,0.0001453176,0.005656293,0.0004046426,0.003032977],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01742043,"threshold_uncertainty_score":0.03463805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01412347846647818,"score_gpt":0.2360930287753807,"score_spread":0.2219695503089026,"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."}}