{"id":"W2293321346","doi":"","title":"COFFEE-FLUX (Costa Rica) Observatory for monitoring and modeling carbon, nutrients, water and sediment ecosystem services in coffee agroforestry systems; Mitigation and adaptation to climate changes through ecosystem manipulation","year":2015,"lang":"en","type":"preprint","venue":"Agritrop (Cirad)","topic":"Water-Energy-Food Nexus Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Ecosystem; Environmental science; Nutrient; Ecosystem services; Adaptation (eye); Carbon sequestration; Agroforestry; Climate change; Ecology; Carbon dioxide; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004747243,0.001150167,0.0007909792,0.0008063525,0.0008351901,0.001544793,0.001364415,0.0008480949,0.009075611],"category_scores_gemma":[0.003334214,0.0002879564,0.0005584889,0.001360232,0.0004490448,0.001024847,0.002136378,0.001069615,0.002208083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002657975,"about_ca_system_score_gemma":0.004818294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1908121,"about_ca_topic_score_gemma":0.1415597,"domain_scores_codex":[0.9990305,0.0003634074,0.00002532819,0.0002038582,0.0002500983,0.0001267857],"domain_scores_gemma":[0.9966941,0.0005262083,0.0002941574,0.0005769294,0.00107227,0.0008363333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003404096,0.0007307416,0.1452401,0.0007913025,0.0005060753,0.0005402182,0.001566581,0.03587426,0.01942108,0.02573902,0.5781412,0.1880453],"study_design_scores_gemma":[0.001501919,0.0003957315,0.2675159,0.0002719527,0.000198421,0.000172743,0.000957269,0.1522008,0.01696038,0.009196055,0.5504245,0.000204347],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.3388771,0.007216301,0.07736563,0.02671734,0.002144529,0.001386754,0.4360127,0.01515991,0.09511968],"genre_scores_gemma":[0.6910961,0.002936628,0.1163418,0.0008055188,0.000660201,0.001048669,0.1335923,0.003753366,0.0497653],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1908121,"threshold_uncertainty_score":0.3794029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05509171281750011,"score_gpt":0.2453225665556861,"score_spread":0.190230853738186,"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."}}