{"id":"W4361197136","doi":"10.5194/ems2023-26","title":"Attributing Venice Acqua Alta events to a changing climate and evaluating the efficacy of MoSE adaptation strategy","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Tropical and Extratropical Cyclones Research","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Flooding (psychology); General Circulation Model; Climate change; Attribution; Adaptation (eye); Environmental resource management; Mediterranean sea; Geography; Sea level rise; Climatology; Environmental planning; Mediterranean climate; Environmental science; Oceanography; Psychology; 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":[0.001616966,0.000312914,0.0003265737,0.0007939315,0.0003622584,0.001257309,0.0004804484,0.0005481045,0.0007877339],"category_scores_gemma":[0.004377887,0.0001146273,0.0005337478,0.0007286626,0.0004989079,0.0005710122,0.0006998005,0.0006405898,0.0000934722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009980663,"about_ca_system_score_gemma":0.0005610142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05012385,"about_ca_topic_score_gemma":0.0692746,"domain_scores_codex":[0.9994112,0.0002477731,0.00002829818,0.0001546828,0.00005845162,0.00009948977],"domain_scores_gemma":[0.9979289,0.0008507037,0.0005454971,0.0002272433,0.0002154983,0.0002322627],"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":[0.0003087917,0.0001565931,0.9390917,0.00004681818,0.0002451088,0.0004608492,0.0003272901,0.04811675,0.001069568,0.000713503,0.0006235783,0.008839416],"study_design_scores_gemma":[0.00002059789,0.0002163835,0.8848864,0.00003019939,0.00008968552,0.00007415625,0.001816078,0.1098156,0.0008916083,0.0005329498,0.001590463,0.00003596013],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980056,0.00004931324,0.0003623936,0.00008935318,0.00001408151,0.00001606384,0.0002836588,0.0000114258,0.001168229],"genre_scores_gemma":[0.9988881,0.00004292338,0.0004393766,0.00002107373,0.00001201491,0.000009380904,0.0004174453,0.000003713839,0.0001659399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05012385,"threshold_uncertainty_score":0.09966415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1725829319078247,"score_gpt":0.3740455815009223,"score_spread":0.2014626495930976,"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."}}