{"id":"W3110791666","doi":"10.3390/rs12244084","title":"Wetland Hydroperiod Change Along the Upper Columbia River Floodplain, Canada, 1984 to 2019","year":2020,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of Canada; Natural Resources Canada; University of Alberta; University of Lethbridge","funders":"U.S. Geological Survey; Environment and Climate Change Canada","keywords":"Floodplain; Wetland; Hydrology (agriculture); Thematic Mapper; Environmental science; Flood myth; Drainage basin; Satellite imagery; Open water; Remote sensing; Physical geography; Geology; Geography; Cartography; Ecology; Oceanography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001340329,0.0001360834,0.0001420082,0.00001032076,0.000298645,0.00009679654,0.0002011631,0.00003081851,0.0003060889],"category_scores_gemma":[0.00002340972,0.0001170707,0.00003605443,0.0002797916,0.00005944521,0.000102857,0.0003819545,0.0001237941,0.0004089109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001875962,"about_ca_system_score_gemma":0.00002775059,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8970706,"about_ca_topic_score_gemma":0.9252267,"domain_scores_codex":[0.9986973,0.0000594038,0.0001526637,0.0003365916,0.0003963808,0.0003576876],"domain_scores_gemma":[0.9994799,0.00002145138,0.00004501153,0.0002569794,0.000008103553,0.0001885636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002982163,0.00001661855,0.01151792,0.00002282169,0.00007379481,0.0002593665,0.005660442,0.003256012,0.007138854,0.000006640824,0.6724941,0.2995236],"study_design_scores_gemma":[0.0004167265,0.00007986496,0.08870961,0.00004545998,0.00006305589,0.00001315458,0.0005190559,0.1520096,0.0005278994,0.00002350797,0.7571255,0.000466546],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.970283,0.00006211382,0.0009256192,0.01993525,0.0003451062,0.0006577278,0.000007070723,0.00005087791,0.007733195],"genre_scores_gemma":[0.9798184,0.00003482018,0.004162313,0.01385916,0.00025353,1.156899e-7,0.000008420265,0.00002633267,0.001836881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2990571,"threshold_uncertainty_score":0.5255859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01304819435865713,"score_gpt":0.2036729494840294,"score_spread":0.1906247551253722,"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."}}