{"id":"W2961186686","doi":"10.1080/15481603.2019.1643530","title":"Separability analysis of wetlands in Canada using multi-source SAR data","year":2019,"lang":"en","type":"article","venue":"GIScience & Remote Sensing","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre For Cold Ocean Resources Engineering","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wetland; Remote sensing; Swamp; Marsh; Environmental science; Synthetic aperture radar; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008309389,0.0001309988,0.0002887834,0.0001326572,0.0000756076,0.00002579098,0.0005426089,0.00002565026,0.000106786],"category_scores_gemma":[0.00004088879,0.0001155385,0.00004355962,0.001836051,0.0001346087,0.0003195691,0.0008169892,0.00009948351,0.000009885948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008744397,"about_ca_system_score_gemma":0.0001783231,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9615972,"about_ca_topic_score_gemma":0.9718105,"domain_scores_codex":[0.9980572,0.00006488052,0.0003207258,0.0006192875,0.0005745293,0.0003634021],"domain_scores_gemma":[0.9987168,0.00004043972,0.0001521048,0.001009013,0.000008917555,0.00007276398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006542243,0.00001869509,0.5030037,0.00001083718,0.00002925077,0.000009273444,0.0002641844,0.4246102,0.02347532,9.022339e-7,0.00004132248,0.04852981],"study_design_scores_gemma":[0.0001277186,0.000006252882,0.1841267,0.0000125869,0.0001038188,8.962653e-7,0.0003466099,0.8143294,0.0003225822,0.00000435353,0.0005001057,0.0001189667],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9806478,0.00001082529,0.017935,0.00004489648,0.0001347597,0.0001818065,0.000006829944,0.000009308149,0.001028743],"genre_scores_gemma":[0.9636039,0.000008401506,0.03615222,0.00007799148,0.000004980127,4.879043e-9,0.00001190235,0.000005803958,0.0001347991],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3897192,"threshold_uncertainty_score":0.4711523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03082083102172585,"score_gpt":0.279000637754777,"score_spread":0.2481798067330512,"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."}}