{"id":"W2003233438","doi":"10.1016/j.watres.2014.01.050","title":"Changes in Escherichia coli to Cryptosporidium ratios for various fecal pollution sources and drinking water intakes","year":2014,"lang":"en","type":"article","venue":"Water Research","topic":"Fecal contamination and water quality","field":"Environmental Science","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cryptosporidium; Indicator bacteria; Fecal coliform; Sewage; Feces; Wastewater; Surface water; Environmental science; Escherichia coli; Pollution; Environmental chemistry; Sewage treatment; Water quality; Veterinary medicine; Environmental engineering; Biology; Microbiology; Chemistry; Ecology; Medicine","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":[0.0004044246,0.0002877802,0.0003054217,0.0006097799,0.0002045839,0.0003765465,0.0002324746,0.0004198456,0.00248177],"category_scores_gemma":[0.001264314,0.0002630431,0.0003526286,0.0006488368,0.0002392421,0.0003127213,0.0002702204,0.0004037999,0.0004926214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002589769,"about_ca_system_score_gemma":0.0001995578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0048288,"about_ca_topic_score_gemma":0.004948282,"domain_scores_codex":[0.9996964,0.00007089726,0.00002523569,0.00008134869,0.00006576833,0.00006038051],"domain_scores_gemma":[0.9991983,0.0002865724,0.0001857276,0.0000613442,0.0001818664,0.00008627437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01647325,0.0003868568,0.7198681,0.0002018559,0.0003791038,0.0002149774,0.0004903736,0.001388512,0.2257492,0.0002729798,0.0005859127,0.03398902],"study_design_scores_gemma":[0.00001549231,0.000766059,0.9680502,0.000004057744,0.0001146862,0.0001298559,0.0002519729,0.0007259108,0.02912386,0.0001151969,0.000690864,0.00001182654],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967463,0.0002177247,0.0006340749,0.00002976107,0.000006743167,0.00001245524,0.001187168,0.0000370038,0.001128724],"genre_scores_gemma":[0.9949168,0.0001851273,0.0007543676,0.00002832669,0.000006544406,0.00002033046,0.0009751811,0.00001260135,0.003100813],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0048288,"threshold_uncertainty_score":0.009601414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04927881787993365,"score_gpt":0.3154501012293222,"score_spread":0.2661712833493886,"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."}}