{"id":"W4214554027","doi":"10.55365/1923.x2020.18.01","title":"Emergy and Water Policy","year":2020,"lang":"en","type":"article","venue":"Review of Economics and Finance","topic":"Sustainability and Ecological Systems Analysis","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Valuation (finance); Scarcity; Process (computing); Value (mathematics); Emergy; Environmental economics; Water scarcity; Government (linguistics); Key (lock); Water supply; Business; Water resources; Environmental resource management; Economics; Computer science; Microeconomics; Environmental science; Sustainable development; Environmental engineering; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001265224,0.00004401623,0.0001941295,0.00000358931,0.00002692149,0.000004267346,0.00004649681,0.00001769888,0.0002207435],"category_scores_gemma":[0.00003510718,0.00003000643,0.00003197667,0.00003860125,0.00006675496,0.00004950106,0.00009944981,0.00001973641,0.00002229747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001553068,"about_ca_system_score_gemma":0.000002466456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000168169,"about_ca_topic_score_gemma":0.00001529387,"domain_scores_codex":[0.9995936,0.0000106506,0.0001664481,0.0001382741,0.0000106356,0.00008042248],"domain_scores_gemma":[0.9998531,0.00000828038,0.00004286407,0.00006312085,0.000002171589,0.00003051815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003402762,0.0001298303,0.1143788,0.011181,0.00008808148,0.000007203173,0.001329456,0.002161996,0.0002741083,0.09122659,0.004120037,0.7750689],"study_design_scores_gemma":[0.0001001281,0.0000808126,0.02114278,0.0001054171,0.00001565287,0.000002238564,0.00002670274,0.002344763,0.0000707876,0.003098723,0.972886,0.0001259579],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9742164,0.0118215,0.000009318654,0.01195102,0.000006105511,0.00009744197,0.000002529722,0.000001989263,0.001893705],"genre_scores_gemma":[0.7146456,0.2833181,0.00006627412,0.001895447,0.00001427645,0.000004097249,6.894356e-7,0.000001491693,0.00005399205],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.968766,"threshold_uncertainty_score":0.2416987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01091868172527648,"score_gpt":0.2040874546783614,"score_spread":0.1931687729530849,"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."}}