{"id":"W2167437752","doi":"10.1126/science.1076978","title":"Arsenic Mobility and Groundwater Extraction in Bangladesh","year":2002,"lang":"en","type":"article","venue":"Science","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":1237,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Institute of Environmental Health Sciences; National Aeronautics and Space Administration","keywords":"Arsenic; Aquifer; Groundwater; Environmental chemistry; Biogeochemical cycle; Dissolved organic carbon; Environmental science; Nitrate; Sorption; Total organic carbon; Chemistry; Geology; Adsorption","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000165776,0.000225196,0.0001925937,0.0008233857,0.0009224913,0.0005837251,0.0002337268,0.0003491366,0.003794124],"category_scores_gemma":[0.0004364095,0.0001791584,0.0001636881,0.001874372,0.0002982503,0.0005464561,0.0006063487,0.0001972006,0.0006819924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002644755,"about_ca_system_score_gemma":0.001347362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07332163,"about_ca_topic_score_gemma":0.07563954,"domain_scores_codex":[0.9998342,0.0000283138,0.00001435702,0.00003060766,0.00004423453,0.0000482948],"domain_scores_gemma":[0.9998511,0.00002304405,0.00005545713,0.000006310068,0.00004392856,0.00002015466],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0019714,0.0004136325,0.7328205,0.0006973202,0.0002382822,0.003969321,0.005429772,0.007736296,0.1489068,0.009962427,0.006004369,0.08184993],"study_design_scores_gemma":[0.0001387299,0.0008445768,0.8592212,0.000163019,0.0001471858,0.002851749,0.01780994,0.004824905,0.04499999,0.009120408,0.0596554,0.0002229032],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9888988,0.00109344,0.0001622866,0.0007572751,0.000005756267,0.00001420745,0.0008275167,0.00001252103,0.008228167],"genre_scores_gemma":[0.996309,0.00117261,0.00007183983,0.00003658276,0.000003656241,0.000009824029,0.000305774,0.000002898753,0.002087875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07332163,"threshold_uncertainty_score":0.1457897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01353596732273618,"score_gpt":0.2369581002417952,"score_spread":0.223422132919059,"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."}}