{"id":"W2125558043","doi":"10.3390/ijerph121012371","title":"Unraveling Health Risk and Speciation of Arsenic from Groundwater in Rural Areas of Punjab, Pakistan","year":2015,"lang":"en","type":"article","venue":"International Journal of Environmental Research and Public Health","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":200,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Agriculture, Faisalabad; Grand Challenges Canada; University of South Australia; Cooperative Research Centre for Contamination Assessment and Remediation of the Environment; COMSATS Institute of Information Technology","keywords":"Groundwater; Arsenic; Genetic algorithm; Water resource management; Arsenic poisoning; Environmental science; Health risk; Environmental health; Geography; Biology; Geology; Ecology; Medicine; Chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.003286408,0.00007167825,0.0001864687,0.0002250655,0.00005113033,0.00003145822,0.0001643245,0.00003629591,0.0002771333],"category_scores_gemma":[0.0001831777,0.00006371963,0.00002817445,0.0001016672,0.0002725938,0.0004022863,0.0001439601,0.0002445964,0.00000442976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000849235,"about_ca_system_score_gemma":0.0001596906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004278073,"about_ca_topic_score_gemma":0.0009840903,"domain_scores_codex":[0.9975535,0.0003506953,0.0006921986,0.0001250924,0.00105964,0.0002188548],"domain_scores_gemma":[0.998866,0.0001668751,0.0005102845,0.00007340252,0.00004135263,0.00034212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001307917,0.0004787775,0.677016,0.000007360456,0.00002906436,0.000005209865,0.005247713,0.00002360573,0.000933602,0.0003041073,0.0002006184,0.3156232],"study_design_scores_gemma":[0.001488834,0.0006746064,0.9828475,0.00006511603,0.000001413594,0.00002323874,0.007490027,0.0005366781,0.0001731661,0.003535224,0.003104206,0.00006001355],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948518,0.0004841607,0.0007263355,0.003450322,0.0000920059,0.0001267009,0.00004050854,0.000001327317,0.0002268606],"genre_scores_gemma":[0.9967119,0.00249223,0.0005468475,0.0001079606,0.00005624367,0.000001322531,0.00002571026,0.000005697057,0.00005214363],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3155632,"threshold_uncertainty_score":0.6467195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05391417699816223,"score_gpt":0.3587245585578864,"score_spread":0.3048103815597242,"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."}}