{"id":"W4210442711","doi":"10.21083/surg.v14i1.6713","title":"Application of LiDAR-Derived Data using Multi-Criteria Evaluation (MCE) and Stochastic Modelling; A Flood Risk Analysis of the Mersey River, Nova Scotia","year":2022,"lang":"en","type":"article","venue":"SURG Journal","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Flood myth; Flooding (psychology); Lidar; Floodplain; Environmental science; Nova scotia; Flood risk assessment; Vulnerability (computing); Hydrology (agriculture); Geographic information system; Water resource management; Environmental resource management; Geography; Remote sensing; Computer science; Cartography; Geology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.001655991,0.00059988,0.0004252027,0.001387244,0.0004526689,0.00147104,0.0006269729,0.0004866725,0.0005733165],"category_scores_gemma":[0.003986564,0.0002599739,0.0005955396,0.0008540343,0.0004701893,0.0003349578,0.0006413651,0.0003904613,0.00004805569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004271342,"about_ca_system_score_gemma":0.002806493,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3848713,"about_ca_topic_score_gemma":0.2919656,"domain_scores_codex":[0.9992803,0.0003230456,0.00003672123,0.00007808883,0.000192415,0.00008953483],"domain_scores_gemma":[0.9980269,0.001172159,0.0002042643,0.0000756326,0.0004296963,0.0000912246],"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":[0.000112532,0.0001294019,0.03706443,0.00006890994,0.00007918011,0.0005742318,0.0001414151,0.9475617,0.001207715,0.001605999,0.0003736754,0.01108081],"study_design_scores_gemma":[0.000007703655,0.0000543458,0.01305869,0.00001545983,0.00001181903,0.00003032965,0.0002521987,0.9856054,0.0003399189,0.0003564771,0.0002525954,0.00001497083],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9782748,0.0001914218,0.01739596,0.0002237596,0.00001418075,0.0001625683,0.0004079716,0.0000412996,0.003287998],"genre_scores_gemma":[0.9932601,0.00006885899,0.005920588,0.00001171344,0.000002812753,0.00003990007,0.0001189534,0.000004998381,0.0005719914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6151286,"threshold_uncertainty_score":0.7652622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06758775751680501,"score_gpt":0.3223116470243105,"score_spread":0.2547238895075055,"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."}}