{"id":"W3123413306","doi":"","title":"Cost Analysis and Water Conservation Potential of Irrigation Technologies in the Texas Panhandle Water Planning Area","year":2010,"lang":"en","type":"article","venue":"2010 Annual Meeting, February 6-9, 2010, Orlando, Florida","topic":"Water resources management and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Environmental science; Water conservation; Mile; Irrigation; Investment (military); Water resource management; Quarter (Canadian coin); Variable cost; Total cost; Hydrology (agriculture); Agricultural economics; Agricultural science; Business; Economics; Geography; Engineering; Ecology; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005203268,0.0004892535,0.0002727557,0.001526366,0.0004580766,0.0008899181,0.000473304,0.0004532967,0.002593462],"category_scores_gemma":[0.001819159,0.0003234593,0.0006093256,0.00197376,0.0003373496,0.001232816,0.0003175957,0.0003047054,0.0001022268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003900325,"about_ca_system_score_gemma":0.001184658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04174022,"about_ca_topic_score_gemma":0.0706035,"domain_scores_codex":[0.9996189,0.0001318484,0.00001150461,0.00003538827,0.0001120496,0.00009026927],"domain_scores_gemma":[0.9988951,0.0007242537,0.0001019302,0.00003759003,0.000188621,0.00005249729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003326134,0.0001526137,0.0241367,0.0000875352,0.00005922843,0.0002275326,0.00004498571,0.9395359,0.001078573,0.003915289,0.001390276,0.02903867],"study_design_scores_gemma":[0.00003629885,0.0003363286,0.04866033,0.00002046953,0.00008127753,0.0001122229,0.0004123317,0.9460461,0.001196109,0.001744168,0.001325816,0.00002851233],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896063,0.0002829358,0.002859661,0.0002432012,0.000008133127,0.0000627734,0.0006244109,0.0000236603,0.006288931],"genre_scores_gemma":[0.996628,0.0001473181,0.001601536,0.00001096765,0.000003714313,0.00003109375,0.0003282779,0.000006453226,0.001242712],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04174022,"threshold_uncertainty_score":0.08299458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01007041372253847,"score_gpt":0.2035517773464674,"score_spread":0.193481363623929,"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."}}