{"id":"W2766469605","doi":"10.1080/19475705.2017.1388854","title":"<i>FloodRisk</i>: a collaborative, free and open-source software for flood risk analysis","year":2017,"lang":"en","type":"article","venue":"Geomatics Natural Hazards and Risk","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Basilicata Regional authority; Ministero dell’Istruzione, dell’Università e della Ricerca","keywords":"Flood myth; Context (archaeology); Risk-based testing; Risk analysis (engineering); Transparency (behavior); Environmental resource management; Risk management; Sustainable development; Flood mitigation; Stakeholder engagement; Computer science; Business; Environmental planning; Software; Software development; Geography; Environmental science; Political science","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0006463454,0.0002771869,0.0004614268,0.00007166904,0.002038641,0.0009059449,0.0009060481,0.00009968977,0.00008104296],"category_scores_gemma":[0.0004571882,0.0002067009,0.000100944,0.0002737822,0.0003119946,0.0006049922,0.00214016,0.0002131807,0.00001092117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003693569,"about_ca_system_score_gemma":0.00001859988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003908358,"about_ca_topic_score_gemma":0.008878535,"domain_scores_codex":[0.998392,0.00008022899,0.0002967953,0.0005402549,0.0003150654,0.0003756757],"domain_scores_gemma":[0.9982358,0.0001443055,0.0005221159,0.0008909212,0.00004425531,0.000162607],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001030354,0.0001712146,0.6900578,0.00006111785,0.001568836,0.000006276409,0.0009761694,0.0009871711,0.00002715602,0.0003102863,0.02167257,0.2840584],"study_design_scores_gemma":[0.004043838,0.0003114183,0.8196459,0.00003193215,0.004064691,0.000002569966,0.0006592254,0.1148344,0.0001353923,0.008328404,0.0471855,0.0007566974],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9827222,0.001013689,0.01263874,0.000413501,0.0002369187,0.001234703,0.0004960508,0.00006513788,0.001179042],"genre_scores_gemma":[0.8607134,0.005849647,0.1300958,0.0001094582,0.00008044801,0.0001098216,0.00005218674,0.00003483879,0.002954428],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2833017,"threshold_uncertainty_score":0.9992605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005485762441152609,"score_gpt":0.2541199437963128,"score_spread":0.2486341813551602,"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."}}