{"id":"W4296673408","doi":"10.5194/iahs2022-234","title":"Evaluating the impact of climate change on water system vulnerabilities using multiple hydrological models&amp;#160;","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Environmental science; Snowmelt; Climate change; Flood myth; Streamflow; Hydrology (agriculture); Climate model; Hydrological modelling; Snow; Drainage basin; Climatology; Environmental resource management; Water resource management; Meteorology; Geography; Ecology","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":[0.001020735,0.0005065802,0.0002807921,0.0005600565,0.0003943182,0.0008510185,0.0006240812,0.0005456195,0.00096755],"category_scores_gemma":[0.001594264,0.0002159095,0.0005680448,0.0006258102,0.0003431629,0.0007957944,0.0004573381,0.0004040495,0.0000558667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00354781,"about_ca_system_score_gemma":0.002503388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3577478,"about_ca_topic_score_gemma":0.4045554,"domain_scores_codex":[0.9997889,0.00008323234,0.000007780212,0.0000339655,0.0000413268,0.00004475218],"domain_scores_gemma":[0.9993514,0.0003286197,0.00007650506,0.00004636082,0.0001106398,0.00008640222],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001380475,0.0001221421,0.07451495,0.00002087695,0.0001275914,0.00008175674,0.00005059152,0.9146731,0.0008416519,0.0008682574,0.0003412137,0.008219728],"study_design_scores_gemma":[0.00001470856,0.00009561998,0.0213323,0.000004795639,0.00005088956,0.00001039096,0.000109396,0.9771743,0.0006360316,0.0003320705,0.0002268434,0.00001258353],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949934,0.00007182836,0.002135063,0.0001667993,0.000008234898,0.00001691202,0.0003848839,0.000069195,0.002153772],"genre_scores_gemma":[0.9977811,0.00004021024,0.001646168,0.00001217659,0.000002801005,0.000007195761,0.0002193035,0.000005418839,0.0002855414],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3577478,"threshold_uncertainty_score":0.711331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2028080220205735,"score_gpt":0.3654439927415379,"score_spread":0.1626359707209644,"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."}}