{"id":"W3145858415","doi":"10.1073/pnas.2020431118","title":"A coupled human–natural system analysis of freshwater security under climate and population change","year":2021,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Water resources management and optimization","field":"Engineering","cited_by":149,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Environment Research Council; Universität Leipzig; Directorate for Geosciences; Bundesministerium für Bildung und Forschung; Deutsche Forschungsgemeinschaft; Stanford Woods Institute for the Environment; Helmholtz-Zentrum für Umweltforschung; Sight Research UK; University of Manchester; Research Councils UK; National Science Foundation","keywords":"Climate change; Natural (archaeology); Population; Environmental change; Geography; Environmental science; Environmental resource management; Ecology; Biology; Sociology; Demography; Archaeology","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":[0.0003545269,0.00005483301,0.0001369465,0.0002169235,0.00007470638,0.00002228514,0.0001443147,0.00003496225,0.000006201126],"category_scores_gemma":[0.00001427825,0.00003932963,0.00004819272,0.0008412027,0.00008908171,0.0002856877,0.00007377194,0.00004782938,8.210721e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002067822,"about_ca_system_score_gemma":9.22786e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001410752,"about_ca_topic_score_gemma":0.000002514045,"domain_scores_codex":[0.9991908,0.000003352245,0.0002077193,0.0001051509,0.0004150774,0.0000779015],"domain_scores_gemma":[0.9997192,0.00001372603,0.0001371819,0.000005820138,0.000113129,0.00001096534],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002498594,0.00007841511,0.3298721,0.003296859,0.001049881,4.564368e-8,0.003924292,0.1760509,0.2682308,0.217107,0.000162385,0.0002023594],"study_design_scores_gemma":[0.0001038859,0.000005650201,0.2862204,0.00007563555,0.0001510947,6.386563e-7,0.0002847312,0.6943236,0.01712271,0.001641269,0.000009557793,0.00006078394],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989729,0.0001555831,0.000003435972,0.0001454769,0.00001257417,0.0000798271,0.00001220261,0.0000172324,0.0006007623],"genre_scores_gemma":[0.999618,0.00002246441,0.0002964871,0.00001876237,0.00002138006,0.000003727737,0.000003218993,0.000002620646,0.00001334498],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5182728,"threshold_uncertainty_score":0.1603816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03034278967338844,"score_gpt":0.2598676290024088,"score_spread":0.2295248393290203,"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."}}