{"id":"W3099746799","doi":"10.3390/rs12223758","title":"The Google Earth Engine Mangrove Mapping Methodology (GEEMMM)","year":2020,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Coastal wetland ecosystem dynamics","field":"Environmental Science","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; University of British Columbia","funders":"U.S. Environmental Protection Agency","keywords":"Mangrove; Environmental resource management; Remote sensing; Carbon stock; Environmental science; Ecosystem services; Earth observation; Climate change; Computer science; Geography; Ecosystem; Satellite; Ecology; Oceanography; Geology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001358465,0.001140835,0.0003171491,0.003738426,0.0003900991,0.001350221,0.001049551,0.000493834,0.004167008],"category_scores_gemma":[0.004535916,0.0003442785,0.0009472544,0.002948742,0.000271831,0.001588072,0.001956483,0.0005228337,0.002233108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002719088,"about_ca_system_score_gemma":0.0008378377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008687559,"about_ca_topic_score_gemma":0.01893093,"domain_scores_codex":[0.9991819,0.0001748435,0.00008064118,0.0001246327,0.0003847399,0.00005326617],"domain_scores_gemma":[0.9985139,0.000392399,0.0002448171,0.0003147717,0.0004716665,0.0000623988],"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":[0.0002720017,0.0001566343,0.05194858,0.00495686,0.0007953509,0.001184439,0.003591695,0.02527141,0.02346059,0.02007873,0.1824824,0.6858012],"study_design_scores_gemma":[0.0001312904,0.0002191967,0.1124325,0.001574292,0.00038677,0.002336803,0.004677899,0.1178275,0.03900672,0.02799541,0.6928695,0.0005419638],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0955281,0.003712774,0.6852345,0.001449627,0.0006352452,0.001768479,0.09935256,0.06514855,0.04717007],"genre_scores_gemma":[0.2940984,0.002430035,0.6412374,0.0003184362,0.0001001773,0.001417837,0.04794692,0.005192185,0.007258704],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008687559,"threshold_uncertainty_score":0.01727396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04130826960860032,"score_gpt":0.2313967338270135,"score_spread":0.1900884642184132,"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."}}