{"id":"W4409791891","doi":"10.1101/2025.04.24.25326374","title":"Benchmarking a massively parallel nucleic acid hybridization platform for monitoring biomarkers of public health significance in wastewater","year":2025,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Children's Hospital of Eastern Ontario","funders":"University of Ottawa","keywords":"Benchmarking; Nucleic acid; Massively parallel; Computational biology; Wastewater; Public health; Computer science; Biotechnology; Business; Chemistry; Biology; Engineering; Medicine; Biochemistry; Waste management; Pathology; Parallel computing; Marketing","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":[0.002896277,0.0009215206,0.0006835486,0.0006905329,0.0004867609,0.001106666,0.001098818,0.001354184,0.001332645],"category_scores_gemma":[0.001992489,0.0004075794,0.0005250789,0.00053159,0.0005847274,0.0007434255,0.001156183,0.0005387492,0.0009135942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008149399,"about_ca_system_score_gemma":0.0007538009,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001764094,"about_ca_topic_score_gemma":0.002130671,"domain_scores_codex":[0.996601,0.0008288217,0.0001822218,0.0008064452,0.00137287,0.0002085546],"domain_scores_gemma":[0.9990863,0.0002114654,0.00008843168,0.0001383866,0.0003858219,0.00008974679],"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":[0.0005113512,0.0002506241,0.003515466,0.0001949924,0.00005053603,0.00005910955,0.00008760536,0.00851417,0.9617184,0.0003366706,0.0004954022,0.02426564],"study_design_scores_gemma":[0.00003501803,0.001475981,0.003656965,0.00001869999,0.00004591849,0.0001152439,0.0000730969,0.08071206,0.9096304,0.0003377463,0.003847953,0.00005103488],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8046625,0.0005809282,0.1831375,0.0005681337,0.0002455515,0.001005435,0.001751478,0.004588456,0.003460001],"genre_scores_gemma":[0.7867752,0.0003544141,0.2062313,0.0002157081,0.00004103827,0.0008813287,0.001887061,0.000165817,0.003448033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002896277,"threshold_uncertainty_score":0.01531714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03943008431061582,"score_gpt":0.3114370442975112,"score_spread":0.2720069599868954,"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."}}