{"id":"W2129248434","doi":"10.1109/eicccc.2006.277248","title":"Adaptation Options for Infrastructure Under Changing Climate Conditions","year":2006,"lang":"en","type":"article","venue":"","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Impact","funders":"","keywords":"Adaptation (eye); Prioritization; Climate change; Risk analysis (engineering); Computer science; Workaround; Environmental resource management; Enforcement; Contingency plan; Climate change adaptation; Critical infrastructure; Environmental planning; Business; Environmental science; Process management; Computer security","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00007418571,0.00005976783,0.00004171123,0.00003902533,0.0002528073,0.00002863195,0.00005226621,0.00002122346,0.001861989],"category_scores_gemma":[0.000001123469,0.00005248383,0.00003105072,0.0001209363,0.00002903935,0.0001731164,0.00006213603,0.00002218582,0.0001144301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006090668,"about_ca_system_score_gemma":0.00000206553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001341577,"about_ca_topic_score_gemma":0.0005258634,"domain_scores_codex":[0.9994799,0.000006338763,0.0000857831,0.0001234897,0.00008880316,0.0002156946],"domain_scores_gemma":[0.9998586,0.00001389007,0.00002881683,0.00007598029,0.000003553239,0.00001915203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.000003335568,0.00005032418,0.002817108,0.000006997625,0.000008436047,3.587608e-7,0.00006614595,0.5396806,0.002082973,0.4169042,0.03658713,0.001792388],"study_design_scores_gemma":[0.001322224,0.0001049054,0.4237908,0.00001204552,0.0001073644,0.000002511428,0.003049933,0.3277004,0.000905422,0.1419837,0.1005085,0.0005121855],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08390473,0.00001219583,0.8320966,0.001129764,0.0002123026,0.0006504414,0.00003540561,0.0001496851,0.08180882],"genre_scores_gemma":[0.9624718,0.00001428593,0.03312279,0.0002580925,0.00005101648,0.00009152421,0.0001649692,0.000007749241,0.003817782],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.878567,"threshold_uncertainty_score":0.9990504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008230551308484584,"score_gpt":0.2438497779566033,"score_spread":0.2356192266481187,"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."}}