{"id":"W1730727702","doi":"10.3390/jmse3031093","title":"A Flood Risk Assessment of the LaHave River Watershed, Canada Using GIS Techniques and an Unstructured Grid Combined River-Coastal Hydrodynamic Model","year":2015,"lang":"en","type":"article","venue":"Journal of Marine Science and Engineering","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nova Scotia Community College","funders":"U.S. Geological Survey","keywords":"Digital elevation model; Bathymetry; Storm surge; Hydrology (agriculture); Flood myth; Discharge; Storm; Estuary; Fluvial; Environmental science; Watershed; Elevation (ballistics); Geology; Flooding (psychology); Drainage basin; Oceanography; Geomorphology; Remote sensing; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007214079,0.0001157211,0.0001576669,0.00007810281,0.0001089732,0.00004170458,0.0002871947,0.00002044108,0.000004245316],"category_scores_gemma":[0.00002316901,0.00007677671,0.00002294998,0.0002241647,0.0002590252,0.0006091581,0.0006502648,0.0001541341,3.075581e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000297736,"about_ca_system_score_gemma":0.0001873442,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05011595,"about_ca_topic_score_gemma":0.01267623,"domain_scores_codex":[0.9987688,0.00001786789,0.0002223613,0.0001449762,0.0006523638,0.0001936078],"domain_scores_gemma":[0.9994807,0.000007776946,0.0001711116,0.0001395518,0.00004530069,0.0001556051],"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":[0.0000237961,0.00004683047,0.1493383,0.00002746347,0.00003566841,0.00002547738,0.0006280549,0.8166073,0.02567444,0.0001303287,0.000124761,0.007337556],"study_design_scores_gemma":[0.0004298096,0.0001361453,0.1060422,0.00001856491,0.00004643604,0.00004379887,0.0001339646,0.8910497,0.001530457,0.0003534189,0.00009910332,0.000116335],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975826,0.000005647675,0.001767267,0.00006233904,0.0001559834,0.0001004266,0.000004329132,0.000006319598,0.0003151588],"genre_scores_gemma":[0.9626104,0.00003446141,0.03729324,0.0000136579,0.00002564797,6.940614e-7,4.844889e-7,0.00000615639,0.00001524697],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07444247,"threshold_uncertainty_score":0.9562094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006081881234497124,"score_gpt":0.2136345876496915,"score_spread":0.2075527064151944,"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."}}