{"id":"W7109114836","doi":"10.1016/j.jag.2025.104994","title":"Hybrid wetland city map: Improved wetland characterization through the synergy of global land cover products","year":2025,"lang":"en","type":"article","venue":"International Journal of Applied Earth Observation and Geoinformation","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China; Key Technologies Research and Development Program; State Key Laboratory of Remote Sensing Science; Ministry of Natural Resources","keywords":"Wetland; Land cover; Cover (algebra); Land use; Characterization (materials science)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0004025092,0.0006070515,0.0003238935,0.003152305,0.0001849372,0.0007654925,0.0003611704,0.0003170003,0.001526666],"category_scores_gemma":[0.0009188754,0.0001542576,0.000530664,0.001734873,0.0001252527,0.0007072661,0.000870603,0.0002453802,0.0006835626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002568198,"about_ca_system_score_gemma":0.0003384618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01026479,"about_ca_topic_score_gemma":0.01736368,"domain_scores_codex":[0.9997475,0.00003088966,0.00001350205,0.00007833415,0.00008818625,0.00004165461],"domain_scores_gemma":[0.9997459,0.00004294001,0.0000332413,0.00004030291,0.0001133535,0.00002426612],"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":[0.0004961395,0.0003544295,0.1332493,0.0003363906,0.0004050148,0.0006741582,0.000522719,0.07848009,0.0533719,0.001461767,0.02380799,0.70684],"study_design_scores_gemma":[0.00005148988,0.0000869655,0.2020211,0.00004808342,0.0001491655,0.0002930197,0.0004829715,0.7469948,0.02551303,0.001445789,0.02280092,0.0001127069],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.713561,0.0004712114,0.2409428,0.0003287336,0.00008968377,0.0003081858,0.02214571,0.01094274,0.01120996],"genre_scores_gemma":[0.7939897,0.0001700467,0.1834705,0.00008084004,0.00003542369,0.000151171,0.01916957,0.0003731011,0.002559738],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01026479,"threshold_uncertainty_score":0.02041006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00722002052632131,"score_gpt":0.2073664258170476,"score_spread":0.2001464052907262,"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."}}