{"id":"W4386807364","doi":"10.1007/s11269-023-03591-0","title":"Flood Subsidence Susceptibility Mapping using Elastic-net Classifier: New Approach","year":2023,"lang":"en","type":"article","venue":"Water Resources Management","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Prince Edward Island","funders":"","keywords":"Topographic Wetness Index; Flood myth; Gradient boosting; Terrain; Hydrogeology; Artificial intelligence; Computer science; Data mining; Geology; Random forest; Remote sensing; Environmental science; Cartography; Digital elevation model; Geography; Geotechnical engineering","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008668447,0.0003260393,0.0002526742,0.0002071895,0.0003407843,0.0002180201,0.0007283531,0.00006953404,0.001643711],"category_scores_gemma":[0.000006518334,0.0002528113,0.0001210225,0.0006806305,0.0001462871,0.0003092956,0.002107379,0.0001641874,0.005363302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002602264,"about_ca_system_score_gemma":0.000003278893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008014558,"about_ca_topic_score_gemma":0.0001254428,"domain_scores_codex":[0.9967922,0.0001156158,0.0004158755,0.0009541969,0.0008172634,0.000904879],"domain_scores_gemma":[0.9989032,0.00001949626,0.00008506931,0.000779905,0.000005266582,0.0002070512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002387534,0.00120359,0.2493736,0.00127991,0.00106424,0.0006484885,0.02240985,0.4394509,0.02226466,0.002116219,0.1930101,0.06693962],"study_design_scores_gemma":[0.001553573,0.00009800959,0.1541115,0.00008656529,0.0002546384,0.000006207628,0.005041883,0.111678,0.0009995459,0.002469385,0.7225333,0.00116741],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8864356,0.00001771069,0.02124588,0.0005165186,0.000277522,0.001029021,0.000002494885,0.0004889597,0.08998629],"genre_scores_gemma":[0.9347982,0.00006530794,0.01710239,0.0002457729,0.0001441669,0.00006057066,0.00006814861,0.00005688049,0.04745858],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5295232,"threshold_uncertainty_score":0.9999924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03775604507704682,"score_gpt":0.2467247965782213,"score_spread":0.2089687515011745,"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."}}