{"id":"W1995348113","doi":"10.1016/j.jchromb.2011.11.042","title":"PCR-ready human DNA extraction from urine samples using magnetic nanoparticles","year":2011,"lang":"en","type":"article","venue":"Journal of Chromatography B","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Urine; Chemistry; genomic DNA; Chromatography; Extraction (chemistry); DNA; DNA extraction; Solid phase extraction; Polymerase chain reaction; Biochemistry; Gene","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0009651663,0.0007986577,0.0005975295,0.0007673085,0.0004926151,0.0005116106,0.0005565595,0.0006903135,0.003171079],"category_scores_gemma":[0.001406995,0.0007518081,0.000819392,0.0003986763,0.0004850234,0.0002742248,0.0004639671,0.00119082,0.002964214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002868046,"about_ca_system_score_gemma":0.0007806337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005180282,"about_ca_topic_score_gemma":0.001517881,"domain_scores_codex":[0.9986795,0.0002604153,0.0001516052,0.0004864817,0.0002564213,0.0001656937],"domain_scores_gemma":[0.9993336,0.0002633054,0.00006866209,0.0001141258,0.0001598893,0.0000604593],"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":[0.0001584611,0.00005365436,0.0004234982,0.0001634309,0.00002563086,0.00006585829,0.00005847461,0.000115368,0.9888124,0.0001803505,0.0004654852,0.009477392],"study_design_scores_gemma":[0.0000286107,0.0001952183,0.001120312,0.00002945518,0.00004798278,0.0002251722,0.0000223367,0.0007529521,0.9901416,0.0001511459,0.007273547,0.00001166979],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2999488,0.003866765,0.6738108,0.0008830706,0.001096297,0.002301698,0.004369251,0.003217802,0.01050542],"genre_scores_gemma":[0.4255779,0.002729854,0.5147918,0.001668107,0.0003788336,0.001957816,0.01668435,0.0005143292,0.035697],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003171079,"threshold_uncertainty_score":0.01060832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03792614713705392,"score_gpt":0.2916067577947655,"score_spread":0.2536806106577116,"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."}}