{"id":"W6966338467","doi":"10.4121/21127528.v1","title":"Wetland Classification with Deep ResU-Net Convolutional Neural Network and Multitemporal Sentinel-1 & 2 Imagery and ALOS Elevation Data: A Case Study in Alberta Parkland & Grassland Natural Region, Canada","year":2022,"lang":"en","type":"dataset","venue":"4TU.ResearchData","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Support vector machine; Elevation (ballistics); Wetland; Random forest; Convolutional neural network; Satellite; Satellite imagery; Grassland","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004758089,0.0006892837,0.000235344,0.0007688971,0.0006925727,0.0007116517,0.0008226004,0.0004619906,0.0004514169],"category_scores_gemma":[0.0005358784,0.0002088731,0.0003811636,0.0009625477,0.0004579345,0.0003547046,0.000316183,0.0003932508,0.0001520706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005763546,"about_ca_system_score_gemma":0.004004589,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.886691,"about_ca_topic_score_gemma":0.9304019,"domain_scores_codex":[0.9997949,0.00002004829,0.000005819192,0.00003987443,0.00005819056,0.00008124932],"domain_scores_gemma":[0.9998168,0.00004048904,0.00001466729,0.00001402497,0.00008421565,0.00002978422],"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":[0.0008163083,0.0007888761,0.3704126,0.0002445899,0.0002893771,0.0057621,0.0009255324,0.3841369,0.01997764,0.001447542,0.009925921,0.2052726],"study_design_scores_gemma":[0.00003688913,0.00007527809,0.1058148,0.00002360796,0.00006610196,0.0002074912,0.001454041,0.8842538,0.005690551,0.000408803,0.001932737,0.00003584872],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9937176,0.0002526901,0.003179559,0.0002811605,0.00001575513,0.00004530977,0.0005577334,0.0002358424,0.001714317],"genre_scores_gemma":[0.9910696,0.0001238139,0.005812841,0.00004439549,0.000006338135,0.000008479875,0.0008033337,0.00001475717,0.002116463],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.113309,"threshold_uncertainty_score":0.2279526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09349743064957579,"score_gpt":0.3367917454669007,"score_spread":0.2432943148173249,"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."}}