{"id":"W4394869789","doi":"10.1002/env.2850","title":"Contamination severity index: An analysis of Bangladesh groundwater arsenic","year":2024,"lang":"en","type":"article","venue":"Environmetrics","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Groundwater contamination; Contamination; Arsenic; Arsenic contamination of groundwater; Statistics; Estimator; Index (typography); Confidence interval; Environmental science; Groundwater; Sample (material); Mathematics; Computer science; Geology; Aquifer; Chemistry; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000814783,0.0002646758,0.000248272,0.002969675,0.0001971781,0.0006279079,0.0001784897,0.0002113746,0.0008468585],"category_scores_gemma":[0.002484358,0.00009992574,0.0003630309,0.004101208,0.0002396805,0.0003386101,0.0005295562,0.0002737874,0.0003429997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006916051,"about_ca_system_score_gemma":0.0003026472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008485383,"about_ca_topic_score_gemma":0.004829273,"domain_scores_codex":[0.9993501,0.0001541063,0.00007530164,0.00009006771,0.000289295,0.00004116442],"domain_scores_gemma":[0.9980888,0.0004779444,0.0006547024,0.000118359,0.000554505,0.0001057308],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002660827,0.00007511007,0.9454234,0.0001018507,0.0002541343,0.0002451717,0.0003320312,0.01055566,0.01063108,0.001080047,0.00118999,0.02984538],"study_design_scores_gemma":[0.000008141296,0.0002017041,0.9532935,0.00001380354,0.0000646902,0.0002808404,0.0007418587,0.03588069,0.005354424,0.001020358,0.003092014,0.00004789092],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9893627,0.0001541298,0.00447162,0.0000773709,0.000006956266,0.00003088162,0.002076762,0.00005440214,0.003765248],"genre_scores_gemma":[0.9969168,0.00006622169,0.001280858,0.00000692604,0.000003411925,0.00001066477,0.001337761,0.000005741938,0.000371447],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008485383,"threshold_uncertainty_score":0.01687199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00944257539418625,"score_gpt":0.2348057939718919,"score_spread":0.2253632185777056,"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."}}