{"id":"W2969455546","doi":"10.3390/w11091773","title":"Trade-Offs between Human and Environment: Challenges for Regional Water Management under Changing Conditions","year":2019,"lang":"en","type":"article","venue":"Water","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Upstream (networking); Downstream (manufacturing); Environmental resource management; Ecosystem; Business; Integrated water resources management; Viewpoints; Environmental science; Midstream; Water resources; Ecosystem services; Natural resource economics; Water quality; Climate change; Land management; Water use; Land use; Environmental planning; Ecology; Computer science; Economics; Environmental 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001947634,0.0001456915,0.0001412741,0.0000602014,0.0003234958,0.00001442991,0.0001071086,0.00005496724,0.001186027],"category_scores_gemma":[1.417921e-7,0.00009277756,0.00004423899,0.00001264209,0.0001613959,0.0001690589,0.0003213498,0.00005430935,0.0008718615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003561791,"about_ca_system_score_gemma":1.348048e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000334366,"about_ca_topic_score_gemma":0.000002569069,"domain_scores_codex":[0.9989291,0.00002342546,0.0001247191,0.0003594324,0.0001194594,0.0004438175],"domain_scores_gemma":[0.9997596,0.00001291258,0.00001589587,0.0001680756,6.459985e-7,0.00004285425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004241089,0.001904126,0.4443732,0.002771052,0.007799895,0.0001821309,0.1337893,0.01239717,0.1759761,0.1540481,0.04215276,0.02418212],"study_design_scores_gemma":[0.003144267,0.000396109,0.2802282,0.00003938624,0.0003557983,0.000007430888,0.002164273,0.00009947349,0.01984821,0.08276051,0.6099556,0.00100069],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9660555,0.00004438846,0.0001518525,0.01735751,0.00007013609,0.0006806761,0.000007253609,0.00004467316,0.01558804],"genre_scores_gemma":[0.9918441,0.0001190102,0.00008728203,0.0006162532,0.00004796796,0.0001084272,0.0001185341,0.00001586213,0.007042628],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5678028,"threshold_uncertainty_score":0.9999061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02796058932447077,"score_gpt":0.2327950833864338,"score_spread":0.204834494061963,"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."}}