{"id":"W2103747227","doi":"10.1002/hyp.1021","title":"A multi‐sensor approach to wetland flood monitoring","year":2002,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; University of Saskatchewan","funders":"National Water Research Institute; University of Calgary","keywords":"Wetland; Environmental science; Delta; Remote sensing; Flood myth; Satellite imagery; Vegetation (pathology); River delta; Hydrology (agriculture); Geography; Geology; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.0003419502,0.0002744722,0.0001758443,0.0008219065,0.0001901843,0.0004648319,0.0003678828,0.0002553687,0.000900595],"category_scores_gemma":[0.0003080769,0.0001571696,0.0001925417,0.0005079846,0.0001088652,0.0003308636,0.0002787,0.000213009,0.00008917493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004152914,"about_ca_system_score_gemma":0.0002663021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008127499,"about_ca_topic_score_gemma":0.01219871,"domain_scores_codex":[0.9998394,0.00004264707,0.000007052229,0.00003343974,0.0000612006,0.00001624337],"domain_scores_gemma":[0.9999002,0.00002432915,0.00001302075,0.00001091586,0.00004244087,0.000009050827],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003546044,0.0003932578,0.0279734,0.0002042907,0.0001859197,0.0002511493,0.0002444643,0.248152,0.1341239,0.002190074,0.002493523,0.5834334],"study_design_scores_gemma":[0.00001576024,0.0001114301,0.03226786,0.0000147997,0.00002928231,0.00005438924,0.0001503971,0.9556486,0.0084133,0.001144382,0.002128171,0.00002164561],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5420303,0.0008545897,0.4473651,0.0003027398,0.0000868698,0.0001857231,0.0009034302,0.000768803,0.007502489],"genre_scores_gemma":[0.8876271,0.0001423225,0.1106286,0.00002656013,0.00002382161,0.0000516339,0.0001994237,0.00001112238,0.001289462],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008127499,"threshold_uncertainty_score":0.01616043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04291185612414479,"score_gpt":0.247689963550745,"score_spread":0.2047781074266002,"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."}}