{"id":"W4409537285","doi":"10.1016/j.rineng.2025.104989","title":"Integrating unsupervised machine learning, statistical analysis, and Monte Carlo simulation to assess toxic metal contamination and salinization in non-rechargeable aquifers","year":2025,"lang":"en","type":"article","venue":"Results in Engineering","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Princess Nourah Bint Abdulrahman University; Magyar Tudományos Akadémia","keywords":"Aquifer; Contamination; Monte Carlo method; Environmental science; Groundwater contamination; Groundwater; Computer science; Geology; Statistics; Geotechnical engineering; Ecology; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005845762,0.0001027959,0.0001856273,0.0003738785,0.000034956,0.00006998285,0.00009678902,0.0000609786,0.000001046396],"category_scores_gemma":[0.001448633,0.0001071216,0.0000127041,0.001058438,0.00000682823,0.0001688815,0.00009059369,0.000170853,1.953886e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005201113,"about_ca_system_score_gemma":0.00001293427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001881231,"about_ca_topic_score_gemma":0.0001713553,"domain_scores_codex":[0.9991363,0.00004439847,0.0002810227,0.0002945345,0.00009006417,0.0001537139],"domain_scores_gemma":[0.9994084,0.0003559601,0.0000369738,0.0001094525,0.00005062483,0.00003858434],"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":[0.000008858512,0.000009323743,0.02332628,0.00004454879,0.00001780297,0.00000414685,0.0006421218,0.9695186,0.00218781,0.0005719487,7.293425e-7,0.003667831],"study_design_scores_gemma":[0.0004014709,0.00001818042,0.0722869,0.00006894016,0.00001220044,3.459221e-7,0.00006735025,0.9259708,0.0009952688,0.00002965036,0.00005862846,0.00009030611],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.307784,0.00004367469,0.691714,0.0001303853,0.00003551918,0.00009845273,0.000003174202,0.00003265038,0.000158122],"genre_scores_gemma":[0.9830551,0.0000107049,0.0167798,0.00001524786,0.000006315444,0.000009527093,0.0000199585,0.000001972689,0.0001014003],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6752711,"threshold_uncertainty_score":0.4368293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01075605442943014,"score_gpt":0.2571851079928814,"score_spread":0.2464290535634512,"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."}}