{"id":"W4413062973","doi":"10.1061/jwrmd5.wreng-6887","title":"Battle of Water Demand Forecasting","year":2025,"lang":"en","type":"article","venue":"Journal of Water Resources Planning and Management","topic":"Water resources management and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Battle; Demand forecasting; Economics; Operations research; Natural resource economics; Environmental science; Water resource management; Engineering; Computer science; History; 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":[0.0003550179,0.0001267616,0.0002169927,0.000418723,0.00006220562,0.00007100841,0.0001474879,0.00003614384,0.00001671005],"category_scores_gemma":[0.000003302991,0.00007734763,0.00005677441,0.00007013466,0.00002648136,0.0001215865,0.0001208834,0.00009405786,0.000001688221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001704916,"about_ca_system_score_gemma":5.687862e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002177553,"about_ca_topic_score_gemma":3.407801e-7,"domain_scores_codex":[0.9991123,0.00002081158,0.0004085187,0.00008868428,0.0001555781,0.0002140876],"domain_scores_gemma":[0.9997605,0.00001765166,0.00005889562,0.00009392453,0.00003152281,0.00003748371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001540751,0.0000478108,0.0080398,0.002252219,0.0009925319,0.0001497224,0.01175577,0.9575343,0.002094012,0.00009652904,0.006878024,0.01000524],"study_design_scores_gemma":[0.004061345,0.0003626802,0.004703293,0.002769195,0.0009088505,0.00006093916,0.003235617,0.1331939,0.09477016,0.001093428,0.7541359,0.0007047004],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9650069,0.0008162198,0.01945862,0.0001443081,0.000304481,0.0001167317,7.009202e-7,0.00003929786,0.01411273],"genre_scores_gemma":[0.9968668,0.0001179396,0.001424808,0.00003187118,0.00006193004,0.000003621215,0.000004292413,0.0000149313,0.001473833],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8243404,"threshold_uncertainty_score":0.3154145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01083097165077679,"score_gpt":0.2009733269139507,"score_spread":0.1901423552631739,"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."}}