{"id":"W2029067082","doi":"10.1016/j.envdev.2013.04.005","title":"Science and management of transboundary lakes: Lessons learned from the global environment facility program","year":2013,"lang":"en","type":"article","venue":"Environmental Development","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick; University of Waterloo","funders":"Russian Academy of Sciences","keywords":"Environmental resource management; Adaptive management; Environmental planning; Business; Climate change; Watershed management; Environmental science; Watershed; Computer science; Ecology","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":[0.01532826,0.0005014093,0.0003868953,0.001050291,0.002862604,0.004287548,0.001429378,0.004432244,0.003259937],"category_scores_gemma":[0.01427153,0.0001688146,0.0004771261,0.001048751,0.005977357,0.005371226,0.008474374,0.006049569,0.0001218379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007480075,"about_ca_system_score_gemma":0.050745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08841075,"about_ca_topic_score_gemma":0.2287797,"domain_scores_codex":[0.9965946,0.001820451,0.0001057456,0.0002281967,0.0006295002,0.0006214819],"domain_scores_gemma":[0.980997,0.009350793,0.0007518107,0.0007558088,0.002939543,0.005205058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003936681,0.00112046,0.05065939,0.0008109604,0.0001334396,0.0009554944,0.008149827,0.005770691,0.001838791,0.1152282,0.1726571,0.642282],"study_design_scores_gemma":[0.0003547097,0.0008741565,0.09680856,0.003356029,0.0001388181,0.0005318007,0.03027196,0.004614735,0.003891949,0.20819,0.6507317,0.0002356442],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.04439114,0.02256302,0.002951061,0.9063291,0.000754968,0.00006254967,0.0001715291,0.00005801263,0.02271861],"genre_scores_gemma":[0.7857806,0.05160599,0.02645531,0.1118215,0.001681693,0.0003804371,0.0005738685,0.00009692486,0.02160361],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08841075,"threshold_uncertainty_score":0.1757923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01831979937872889,"score_gpt":0.2271669462966416,"score_spread":0.2088471469179127,"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."}}