{"id":"W2772365113","doi":"10.3390/rs9121315","title":"Google Earth Engine, Open-Access Satellite Data, and Machine Learning in Support of Large-Area Probabilistic Wetland Mapping","year":2017,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":297,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Biodiversity Monitoring Institute; University of Calgary","funders":"Alberta Biodiversity Monitoring Institute","keywords":"Computer science; Wetland; Workflow; Remote sensing; Environmental science; Cloud computing; Geospatial analysis; Earth observation; Digital elevation model; Data mining; Satellite; Database; Geography","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":[0.00399648,0.001836652,0.0009687573,0.003638788,0.0008234803,0.00275136,0.003766026,0.0008334848,0.00384081],"category_scores_gemma":[0.01510598,0.0009226676,0.001771114,0.004195686,0.0009465042,0.003457525,0.002966749,0.001935066,0.003567508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001486537,"about_ca_system_score_gemma":0.004175337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1149593,"about_ca_topic_score_gemma":0.141935,"domain_scores_codex":[0.998358,0.0002955321,0.0001455181,0.0003669948,0.0006784812,0.0001554737],"domain_scores_gemma":[0.9952416,0.001679435,0.0003587714,0.001336532,0.001046926,0.0003367322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001076833,0.0004245386,0.03218727,0.001349638,0.0009084335,0.001323837,0.001338968,0.2224035,0.009806728,0.04724218,0.2073421,0.4745959],"study_design_scores_gemma":[0.0001130486,0.00005917854,0.00899166,0.00009928116,0.00007725745,0.0001666986,0.0002392723,0.8957905,0.007042675,0.04259767,0.04467481,0.000147991],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04381456,0.001114292,0.5682951,0.003499889,0.0003495537,0.0007070419,0.02356347,0.3453825,0.01327348],"genre_scores_gemma":[0.2833037,0.0008113937,0.6563193,0.000513672,0.0001127729,0.0004829599,0.04443559,0.01016383,0.003856833],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1149593,"threshold_uncertainty_score":0.2285803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05561008696326232,"score_gpt":0.3009716883399764,"score_spread":0.2453616013767141,"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."}}