{"id":"W3204721907","doi":"10.1039/d1ew00539a","title":"Development of a rapid pre-concentration protocol and a magnetic beads-based RNA extraction method for SARS-CoV-2 detection in raw municipal wastewater","year":2021,"lang":"en","type":"article","venue":"Environmental Science Water Research & Technology","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Acadia University; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Dalhousie University; Canadian Water Network; University of Alberta","keywords":"Extraction (chemistry); Wastewater; Magnetic bead; Chromatography; RNA extraction; RNA; Raw material; Magnetic nanoparticles; Chemistry; Materials science; Waste management; Nanotechnology; Nanoparticle; Biochemistry; 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":[0.001045965,0.000988247,0.0005700725,0.0006656626,0.0004081744,0.0005109035,0.0005162575,0.0008355826,0.0009647626],"category_scores_gemma":[0.0009153813,0.0005265694,0.0005925032,0.0002978014,0.0004390409,0.0003968569,0.0004284044,0.0009657484,0.001007048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003499447,"about_ca_system_score_gemma":0.001145302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008820099,"about_ca_topic_score_gemma":0.002182778,"domain_scores_codex":[0.9987572,0.0002286649,0.0001375896,0.0002267236,0.000558242,0.00009142229],"domain_scores_gemma":[0.9995502,0.0001258812,0.00007700792,0.00006315769,0.0001515412,0.00003219982],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001269036,0.00001794247,0.00009335043,0.00005485497,0.000003812104,0.00001925378,0.00001030381,0.00006663417,0.9971793,0.00004309658,0.00004155374,0.002457228],"study_design_scores_gemma":[0.000007516197,0.0001682304,0.001420119,0.000009929681,0.0000143467,0.0001440063,0.00001580505,0.001096292,0.9939855,0.000062924,0.003058501,0.00001694352],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4226257,0.004092608,0.5602437,0.0009182388,0.0005012467,0.003000877,0.001832766,0.001934193,0.004850606],"genre_scores_gemma":[0.3775856,0.002741122,0.6060204,0.0006028278,0.0001319119,0.002557109,0.003654174,0.0001954458,0.006511372],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001045965,"threshold_uncertainty_score":0.005531609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06556539758412126,"score_gpt":0.4016659011671016,"score_spread":0.3361005035829803,"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."}}