{"id":"W2340783352","doi":"10.5070/g313927488","title":"Adaptive Capacity for eutrophication governance of the Laurentian Great Lakes","year":2016,"lang":"en","type":"article","venue":"Electronic Green Journal","topic":"Transboundary Water Resource Management","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Eutrophication; Adaptive capacity; Environmental science; Ecosystem; Corporate governance; Nutrient; Freshwater ecosystem; Sewage; Lake ecosystem; Environmental resource management; Water resource management; Environmental protection; Hydrology (agriculture); Ecology; Climate change; Environmental engineering; Business; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001709496,0.0001353625,0.000077531,0.0004149901,0.003256072,0.002427357,0.0003526616,0.0003948317,0.0009668105],"category_scores_gemma":[0.001878918,0.00009205822,0.00006324072,0.0003102554,0.007603738,0.001164237,0.002332073,0.000544407,0.00003088197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006118644,"about_ca_system_score_gemma":0.004569663,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07654203,"about_ca_topic_score_gemma":0.2474744,"domain_scores_codex":[0.999189,0.0003895664,0.00002101576,0.00008293067,0.00009864946,0.0002189435],"domain_scores_gemma":[0.9992408,0.0002580763,0.0001719759,0.00004566113,0.00007862841,0.0002048569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00003329601,0.0000461583,0.0606729,0.00004946573,0.00001554678,0.00174729,0.8386847,0.001037524,0.002990308,0.0691985,0.002205923,0.0233184],"study_design_scores_gemma":[0.000007577059,0.00006904154,0.1377701,0.0001014052,0.000007276974,0.0003501775,0.7832623,0.001190483,0.0004852901,0.0110382,0.06567764,0.00004055064],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9752219,0.0001046442,0.000413809,0.003009517,0.000004151161,0.00001332716,0.000009741262,0.000004097485,0.02121889],"genre_scores_gemma":[0.9991488,0.00004237223,0.0001554636,0.00006409655,0.000001184506,0.000004026365,0.000002896445,7.795824e-7,0.0005802455],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.923458,"threshold_uncertainty_score":0.152193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01845687149225173,"score_gpt":0.2400290184303743,"score_spread":0.2215721469381225,"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."}}