{"id":"W2019212493","doi":"10.1016/j.jala.2007.10.008","title":"An Instrument for Automated Purification of Nucleic Acids from Contaminated Forensic Samples","year":2008,"lang":"en","type":"article","venue":"JALA Journal of the Association for Laboratory Automation","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Canadian Mounted Police; University of British Columbia","funders":"National Human Genome Research Institute","keywords":"Nucleic acid; Contamination; Nucleic acid quantitation; Chromatography; Chemistry; Sample preparation; Denim; Environmental chemistry; Materials science; Biology; Biochemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005086737,0.0000921488,0.0001666082,0.00004816199,0.0001661008,0.00001209034,0.0002195208,0.0002026865,0.000001754844],"category_scores_gemma":[0.0003581528,0.00007522354,0.0001384096,0.0001308887,0.00004095382,0.0000202863,0.00001546889,0.00005377028,3.259978e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000917505,"about_ca_system_score_gemma":0.0001492472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004789736,"about_ca_topic_score_gemma":0.000005869168,"domain_scores_codex":[0.9990471,0.0001233591,0.0004567922,0.0001256932,0.0001445252,0.0001025251],"domain_scores_gemma":[0.9973795,0.00004883593,0.001303048,0.0002327093,0.001003447,0.00003246181],"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":[0.00006837409,0.00009868069,0.01147076,0.000009225814,0.0001208614,4.887562e-8,0.00008766034,0.0001309949,0.9832451,0.000716585,0.003500877,0.000550854],"study_design_scores_gemma":[0.001016384,0.0003935673,0.1345317,0.00002011324,0.00009063222,0.000002940742,0.00005057407,0.00350499,0.8472328,0.0006068011,0.01244312,0.0001064068],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9710844,0.00005985469,0.02743212,0.000369208,0.0001393425,0.000480543,0.0003925618,0.00003270405,0.000009323835],"genre_scores_gemma":[0.9798858,0.00003699996,0.0193471,0.0001303229,0.0001036371,0.00005794611,0.0003988948,0.0000149359,0.00002440569],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1360123,"threshold_uncertainty_score":0.3067527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01072037697405095,"score_gpt":0.2584935612509224,"score_spread":0.2477731842768715,"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."}}