{"id":"W3034823224","doi":"10.23977/acss.2020.040105","title":"Classification of Groundwater Quality using Artificial Neural Networks in Safwan and Al-Zubayr in Basra","year":2020,"lang":"en","type":"article","venue":"Advances in Computer Signals and Systems","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Groundwater; Artificial neural network; Groundwater resources; Water resource management; Environmental science; Environmental resource management; Hydrology (agriculture); Computer science; Artificial intelligence; Engineering; Aquifer; Geotechnical engineering","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":[0.0005521563,0.00009696159,0.000253956,0.00003130964,0.0000265234,0.00003751166,0.00009972,0.00005471843,0.000004681443],"category_scores_gemma":[0.00001487651,0.00008279332,0.00001399919,0.0002251705,0.0001053045,0.0002674799,0.0001120989,0.0001197217,6.009167e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003781212,"about_ca_system_score_gemma":0.000002114703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005041044,"about_ca_topic_score_gemma":0.000228986,"domain_scores_codex":[0.9986423,0.0002671844,0.0004743084,0.0003164306,0.0001248871,0.0001749005],"domain_scores_gemma":[0.9996174,0.0001235013,0.0001230785,0.00008307885,0.000003831187,0.00004912527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001876382,0.00002986597,0.2363508,0.00002848263,8.43981e-7,0.000006248169,0.0003014914,0.7431354,0.001716694,0.0001237595,0.000001904792,0.0182858],"study_design_scores_gemma":[0.0001504058,0.00008132298,0.06327588,0.00005173005,8.109345e-7,0.000003250099,0.00001924501,0.9359455,0.00001764226,0.0003028046,0.00006231067,0.00008914343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9064235,0.0004737559,0.09259871,0.0002027447,0.0001176868,0.0001470667,6.984547e-7,0.00000890938,0.00002694093],"genre_scores_gemma":[0.9983266,0.00002601787,0.001393908,0.0001997875,0.00004370849,0.000003930443,0.000001246358,0.000004431993,3.783375e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1928101,"threshold_uncertainty_score":0.3376214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08178138337406413,"score_gpt":0.3093908973227107,"score_spread":0.2276095139486466,"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."}}