{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004184798,0.000113411,0.0001669471,0.000509476,0.00005588468,0.00003659615,0.000141645,0.00009772962,0.004790302],"category_scores_gemma":[0.00004810723,0.0001099179,0.000121346,0.002152226,0.0001301741,0.0004978764,0.00007921148,0.0001154616,0.0002243721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002790025,"about_ca_system_score_gemma":0.00000684937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002177773,"about_ca_topic_score_gemma":0.0002549772,"domain_scores_codex":[0.9987701,0.00007737915,0.0002609357,0.0003247731,0.0004143219,0.0001524899],"domain_scores_gemma":[0.9994937,0.0001003605,0.00006851186,0.0002536559,0.000005467746,0.00007831443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001285796,0.0003645696,0.6148782,0.00002348307,0.0003115071,0.00002083454,0.002611289,0.005197402,0.007095365,0.001850303,0.0004577313,0.3671764],"study_design_scores_gemma":[0.00009910079,0.00005131533,0.8547041,0.000003010267,0.0002737553,0.000002143773,0.000141687,0.1299428,0.001054362,0.0001403558,0.01345323,0.0001340696],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9511042,0.0000705581,0.04530776,0.00007387373,0.0001332544,0.0001173154,0.00001423834,0.00005646639,0.00312234],"genre_scores_gemma":[0.9970374,0.00004465454,0.0004050588,0.00007709894,0.00002044651,0.000007945766,0.0001228332,0.00001249076,0.002272082],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3670424,"threshold_uncertainty_score":0.9961194,"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."}}