{"id":"W4392288334","doi":"10.18280/ijdne.190136","title":"Artificial Neural Network Assessment of Groundwater Quality for Agricultural Use in Babylon City: An Evaluation of Salinity and Ionic Composition","year":2024,"lang":"en","type":"article","venue":"International Journal of Design & Nature and Ecodynamics","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Baghdad","keywords":"Salinity; Artificial neural network; Groundwater; Agriculture; Composition (language); Water resource management; Environmental science; Water quality; Hydrology (agriculture); Agricultural engineering; Engineering; Environmental engineering; Geography; Computer science; Artificial intelligence; Geology; Archaeology; Geotechnical engineering; Ecology; Oceanography; Philosophy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006770432,0.0005899989,0.0004844934,0.001043468,0.0001832554,0.0005547201,0.0003981231,0.0004349565,0.0004830656],"category_scores_gemma":[0.001232938,0.0001755331,0.0003336371,0.001187688,0.0002073713,0.0002810157,0.0003384637,0.0002324343,0.0001459917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001212634,"about_ca_system_score_gemma":0.0006015988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04008803,"about_ca_topic_score_gemma":0.03260383,"domain_scores_codex":[0.9997035,0.00008637687,0.00003035166,0.00005991573,0.0000771027,0.00004273315],"domain_scores_gemma":[0.9995707,0.0001255343,0.00009370094,0.00001611329,0.0001734704,0.00002049051],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001135204,0.0004283819,0.6971662,0.0003187106,0.0003605587,0.0005860432,0.0004615725,0.185465,0.01690192,0.0002967739,0.001425751,0.09545386],"study_design_scores_gemma":[0.00003119188,0.0005486632,0.3195901,0.00004877201,0.0001278698,0.0001063796,0.0008894457,0.6713416,0.006207916,0.0001836185,0.0008777886,0.00004668144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958175,0.0001030385,0.003120377,0.0000429007,0.00001204715,0.00002371304,0.0002375218,0.00003813077,0.0006049513],"genre_scores_gemma":[0.9969988,0.0001120658,0.00189318,0.000008626892,0.000002918655,0.00002567072,0.0004518085,0.000003326804,0.0005037265],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04008803,"threshold_uncertainty_score":0.07970935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0755148038975269,"score_gpt":0.3732045015101441,"score_spread":0.2976896976126172,"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."}}