{"id":"W2117591948","doi":"10.3968/j.css.1923669720050103.011","title":"A Study on Water Utilization in Chinese Rural Areas","year":2009,"lang":"en","type":"article","venue":"Canadian social science","topic":"Water Resources and Sustainability","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Government (linguistics); Resource (disambiguation); Population; Agriculture; Rural area; Investment (military); Economic shortage; Business; Irrigation; Water resources; Ideology; Economic growth; Agricultural economics; Natural resource economics; Economics; Political science; Geography; Sociology; Politics; Law","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":[0.0004344351,0.0000794602,0.00007542734,0.00008056297,0.0003902338,0.00006946117,0.000302443,0.00002730282,0.000236741],"category_scores_gemma":[0.00003706203,0.000055695,0.00001914124,0.0006431657,0.0002591758,0.0001954396,0.00003625443,0.00007328589,0.00007997818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001097138,"about_ca_system_score_gemma":0.00004090892,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03120665,"about_ca_topic_score_gemma":0.07329237,"domain_scores_codex":[0.9988415,0.00003741946,0.00009815353,0.0002387853,0.000297948,0.0004862428],"domain_scores_gemma":[0.999621,0.000003488221,0.00001144503,0.0001235947,0.000008110409,0.0002324073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000004651558,0.00006959361,0.9812545,3.115059e-7,2.466595e-7,0.00002615612,0.01166677,0.00004340359,0.0002566313,0.00009757096,0.00005193327,0.0065283],"study_design_scores_gemma":[0.000123357,0.00007830535,0.9934074,9.004272e-7,6.30879e-7,5.472962e-7,0.00415775,0.00005362506,0.00004588714,0.0007643201,0.001279062,0.00008819853],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9316089,8.008624e-7,0.000001179956,0.0006410737,0.00003400547,0.0002389866,0.000001162266,0.000009906153,0.06746401],"genre_scores_gemma":[0.9991947,9.710144e-8,0.000001895972,0.0005492949,0.00002522694,0.000004969747,0.000001191035,0.000002381892,0.0002201968],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06758587,"threshold_uncertainty_score":0.9752446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01200375905545498,"score_gpt":0.257271238013782,"score_spread":0.245267478958327,"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."}}