{"id":"W3203170306","doi":"10.3390/rs13193878","title":"Remote Sensing of Wetlands in the Prairie Pothole Region of North America","year":2021,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ducks Unlimited Canada; University of Lethbridge; Alberta Environment and Protected Areas","funders":"Mitacs","keywords":"Remote sensing; Wetland; Geospatial analysis; Environmental science; Ground truth; Vegetation (pathology); Earth observation; Synthetic aperture radar; Aerial survey; Satellite; Computer science; Geography; Ecology; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0002837183,0.0001610271,0.0001210091,0.0007866162,0.0002855882,0.0002948056,0.000237328,0.000152543,0.0004139271],"category_scores_gemma":[0.0003908669,0.0001073648,0.0001290988,0.001111534,0.0001500188,0.0005415027,0.0003555854,0.0001941121,0.00008823836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002307988,"about_ca_system_score_gemma":0.0003436774,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04379482,"about_ca_topic_score_gemma":0.1329158,"domain_scores_codex":[0.9998477,0.00002254578,0.00001149452,0.00004109843,0.00006326281,0.000013958],"domain_scores_gemma":[0.9998341,0.00003916843,0.00003304046,0.00001500322,0.00006668172,0.0000120733],"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":[0.0001606533,0.0001971184,0.3042823,0.001089624,0.0001631444,0.001051258,0.001911874,0.01501285,0.1368809,0.001817387,0.007767911,0.5296649],"study_design_scores_gemma":[0.00001664369,0.00006027429,0.9669799,0.0001083004,0.00004675865,0.0003562356,0.0008162133,0.01383364,0.003792523,0.0003327582,0.01362486,0.00003190586],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9700812,0.004205222,0.01279925,0.0003860335,0.00004710793,0.0001170417,0.003001421,0.000287977,0.009074774],"genre_scores_gemma":[0.9627739,0.002658045,0.0306972,0.00008961977,0.00002090387,0.00006883862,0.002062702,0.00001803077,0.001610772],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9562052,"threshold_uncertainty_score":0.08707982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01497985271969689,"score_gpt":0.2384277299727818,"score_spread":0.2234478772530849,"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."}}