{"id":"W4214674200","doi":"10.1080/10643389.2022.2039549","title":"Colloidal lead in drinking water: Formation, occurrence, and characterization","year":2022,"lang":"en","type":"article","venue":"Critical Reviews in Environmental Science and Technology","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lead (geology); Colloid; Environmental science; Water quality; Nanotechnology; Environmental chemistry; Chemistry; Environmental engineering; Materials science; Geology","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":[],"consensus_categories":[],"category_scores_codex":[0.0008739062,0.00007735737,0.0001211296,0.0001781314,0.0002937673,0.00001795218,0.0001566818,0.00003434311,0.0004392935],"category_scores_gemma":[0.0001211293,0.00006846736,0.000007518659,0.0005064763,0.001192014,0.0004720235,0.0005721598,0.0001667305,0.0000298313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003280713,"about_ca_system_score_gemma":0.000005916017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005629464,"about_ca_topic_score_gemma":0.00002439816,"domain_scores_codex":[0.9989148,0.00004935146,0.0002523995,0.0002969898,0.0002382316,0.0002482689],"domain_scores_gemma":[0.9998083,0.00001878246,0.00002980706,0.00009861371,0.000001773726,0.00004278003],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000003120017,0.00009680021,0.1118437,0.00001156714,2.159335e-7,0.000007242867,0.0007395049,0.000002345923,0.4061672,0.002712145,0.0000182973,0.4783978],"study_design_scores_gemma":[0.00190294,0.00060893,0.4737058,0.000150242,0.00001985406,0.0004102827,0.005513773,0.01327651,0.04459276,0.01383083,0.4448488,0.001139287],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971011,0.0001946444,0.0001415247,0.001752935,0.00004777421,0.0002970971,0.000004592444,0.00001270209,0.0004476374],"genre_scores_gemma":[0.9986386,0.0007527758,0.0001537272,0.0002829299,0.000002301894,0.0001194325,0.00001366987,0.00000213761,0.00003444033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4772585,"threshold_uncertainty_score":0.4809956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009849408474711305,"score_gpt":0.2471234324795667,"score_spread":0.2372740240048554,"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."}}