{"id":"W2743298634","doi":"10.1002/rse2.59","title":"Satellite remote sensing of ecosystem functions: opportunities, challenges and way forward","year":2017,"lang":"en","type":"article","venue":"Remote Sensing in Ecology and Conservation","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":313,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Environment Research Council; Sight Research UK","keywords":"Ecosystem services; Biodiversity; Environmental resource management; Ecosystem; Remote sensing; Ecosystem health; Business; Environmental planning; Environmental science; Ecology; Geography; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005517537,0.0001162924,0.0002375019,0.00005364498,0.0002996532,0.0000332229,0.00005926931,0.0001518341,0.000009025356],"category_scores_gemma":[0.00005746314,0.0001082023,0.00002071827,0.0000283824,0.00007291425,0.0002516046,0.0001016705,0.00008378596,0.00001098253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004426239,"about_ca_system_score_gemma":0.00001234308,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002001213,"about_ca_topic_score_gemma":0.07300042,"domain_scores_codex":[0.9990878,0.0001118589,0.0002843145,0.0002525999,0.00007899319,0.0001844966],"domain_scores_gemma":[0.9992653,0.0001301638,0.0002677028,0.0002654343,0.00002049682,0.00005089349],"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":[0.00005162507,0.000006913807,0.02839484,0.00018602,0.00002488105,0.00003716104,0.0009754054,0.00002595362,0.0006555099,0.00004009486,0.00001932467,0.9695823],"study_design_scores_gemma":[0.000649708,0.00008887218,0.759084,0.0003463568,0.00004298703,0.0001933059,0.0009867126,0.2271324,0.0002525246,0.003930465,0.007062213,0.0002303689],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926184,0.0004729826,0.0002068708,0.00302175,0.0002077169,0.0001495476,0.000002405648,0.00001802228,0.003302334],"genre_scores_gemma":[0.9935557,0.00446838,0.001663932,0.0001883083,0.00003007204,3.251287e-8,0.000005862218,0.00000872565,0.00007902017],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9693519,"threshold_uncertainty_score":0.9439149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04386216005471455,"score_gpt":0.2354151607461694,"score_spread":0.1915530006914549,"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."}}