{"id":"W2515827384","doi":"10.5194/nhess-17-765-2017","title":"Costs of sea dikes – regressions and uncertainty estimates","year":2017,"lang":"en","type":"article","venue":"Natural hazards and earth system sciences","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Seventh Framework Programme; Leibniz-Gemeinschaft; Engineering and Physical Sciences Research Council","keywords":"Dike; Regression; Probabilistic logic; Function (biology); Range (aeronautics); Regression analysis; Econometrics; Linear regression; Unit (ring theory); Statistics; Computer science; Mathematics; Geology; Engineering","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":[0.01336016,0.001107514,0.000828355,0.003434629,0.0003396782,0.002539492,0.001939251,0.0009601607,0.002904061],"category_scores_gemma":[0.08422696,0.0006744591,0.001963523,0.004298414,0.001136117,0.003246167,0.001267528,0.002192114,0.0003834495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00318986,"about_ca_system_score_gemma":0.0008334364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01292028,"about_ca_topic_score_gemma":0.006123559,"domain_scores_codex":[0.991563,0.004620512,0.0005083012,0.001049622,0.001842169,0.0004163471],"domain_scores_gemma":[0.859144,0.1234975,0.008383542,0.004799418,0.003962449,0.000213026],"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":[0.0001060689,0.00003935429,0.02179967,0.0001555273,0.0002035259,0.0000967682,0.0001073963,0.9371167,0.0002529867,0.01953933,0.0008222783,0.01976032],"study_design_scores_gemma":[0.00001167076,0.00009620864,0.03628329,0.0001735174,0.00009121926,0.0002093515,0.000247214,0.9276983,0.001701689,0.0305671,0.002799817,0.0001205575],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.534274,0.003718103,0.4405542,0.001486818,0.00009279911,0.0003298937,0.005567485,0.000430609,0.01354614],"genre_scores_gemma":[0.9530157,0.0008619928,0.04199098,0.00006567217,0.00002940054,0.000186823,0.002013479,0.0001352933,0.001700596],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01336016,"threshold_uncertainty_score":0.07065612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01108750865712742,"score_gpt":0.2780540580393692,"score_spread":0.2669665493822417,"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."}}