{"id":"W3119988103","doi":"10.1016/j.jclepro.2021.125942","title":"Synergetic management of energy-water nexus system under uncertainty: An interval bi-level joint-probabilistic programming method","year":2021,"lang":"en","type":"article","venue":"Journal of Cleaner Production","topic":"Water-Energy-Food Nexus Studies","field":"Environmental Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Regina","funders":"National Key Research and Development Program of China; Chinese Academy of Sciences","keywords":"Probabilistic logic; Water-energy nexus; Computer science; Interval (graph theory); Time horizon; Electricity; Mathematical optimization; Hydropower; Nexus (standard); Operations research; Environmental economics; Engineering; Economics; Mathematics; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002474902,0.0009890551,0.001106678,0.0009113855,0.0005828472,0.00168156,0.001651091,0.001146613,0.004005386],"category_scores_gemma":[0.003362396,0.0007862636,0.001534225,0.001255281,0.0007154943,0.001587393,0.00163527,0.001682168,0.0002294465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001087307,"about_ca_system_score_gemma":0.002619483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008686018,"about_ca_topic_score_gemma":0.005869254,"domain_scores_codex":[0.9988853,0.0004942574,0.00004849947,0.0001788229,0.0002455436,0.0001476372],"domain_scores_gemma":[0.9984726,0.0009982863,0.0001547971,0.00004611026,0.0002518561,0.00007625663],"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":[0.00001959407,0.00002392282,0.0005143197,0.00005354956,0.00003464714,0.00006551407,0.00004496863,0.9776747,0.0002720151,0.01231814,0.0003724008,0.008606326],"study_design_scores_gemma":[0.000003604469,0.000009779013,0.00005568846,0.000005413385,0.000007562222,0.000006767157,0.00001089939,0.9955645,0.00005283909,0.004021187,0.000258378,0.000003483471],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01009784,0.0002088246,0.9850114,0.0001928683,0.00002407464,0.00006770451,0.0000914,0.00009716293,0.004208817],"genre_scores_gemma":[0.6259718,0.0007173739,0.3671061,0.0002141808,0.00008032179,0.0007130984,0.0003847523,0.0001279994,0.004684356],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008686018,"threshold_uncertainty_score":0.01727092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04151386112774465,"score_gpt":0.2601906202220719,"score_spread":0.2186767590943273,"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."}}