{"id":"W2889670723","doi":"10.1007/s11269-018-2107-1","title":"Surface Water Quantity for Drinking Water during Low Flows - Sensitivity Assessment Solely from Climate Data","year":2018,"lang":"en","type":"article","venue":"Water Resources Management","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Environmental science; Climate change; Water supply; Climate model; Sensitivity (control systems); Water resources; Surface water; Streamflow; Water use; Hydrology (agriculture); Hydrogeology; Water resource management; Climatology; Econometrics; Drainage basin; Geography; Environmental engineering; Mathematics; Geology; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001880663,0.0003524233,0.0004404301,0.000648588,0.0001769321,0.0005715273,0.0003786357,0.0003917595,0.000790914],"category_scores_gemma":[0.005007126,0.0003069036,0.0009142796,0.0008155082,0.0002459133,0.001355865,0.0005243442,0.0003233964,0.0001731001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005134186,"about_ca_system_score_gemma":0.0004411223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01974714,"about_ca_topic_score_gemma":0.01501349,"domain_scores_codex":[0.9991648,0.0004386667,0.00004970235,0.0001594082,0.000134221,0.00005322346],"domain_scores_gemma":[0.9975359,0.001581765,0.0001337884,0.0004189134,0.0002809339,0.00004873475],"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":[0.001400129,0.0002693651,0.4770541,0.0003525206,0.0008537673,0.0002248271,0.0002466285,0.4549904,0.01992835,0.001353635,0.001891388,0.04143479],"study_design_scores_gemma":[0.00008513797,0.0003538418,0.5283758,0.00004649897,0.0004167101,0.0001008834,0.0001912767,0.4408889,0.02355264,0.0028591,0.003048615,0.00008061501],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9778766,0.0001200727,0.01253155,0.0001508497,0.0000246399,0.0000863396,0.005177136,0.0001655704,0.003867226],"genre_scores_gemma":[0.9958085,0.00003122264,0.002109888,0.00002370104,0.000008910331,0.0000230499,0.001728358,0.00002302529,0.0002433242],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01974714,"threshold_uncertainty_score":0.03926438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02145028700255952,"score_gpt":0.2547262287822159,"score_spread":0.2332759417796564,"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."}}