{"id":"W3015562057","doi":"10.17504/protocols.io.7ejhjcn","title":"Phenol/Chloroform Genomic DNA extraction from Tissue Culture cells v1","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia Hospital","funders":"","keywords":"genomic DNA; DNA; Nanopore sequencing; Chloroform; Phenol; DNA extraction; Chromatography; Chemistry; Computational biology; Combinatorial chemistry; Nanotechnology; DNA sequencing; Biology; Materials science; Biochemistry; Gene; Organic chemistry; Polymerase chain reaction","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":[0.001164189,0.001891915,0.001470702,0.0020678,0.001567163,0.001085868,0.002230818,0.001069004,0.05222621],"category_scores_gemma":[0.001524582,0.001036195,0.001377925,0.002014126,0.0009490602,0.0007013822,0.001420126,0.004248192,0.07329094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006743405,"about_ca_system_score_gemma":0.00114428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00269835,"about_ca_topic_score_gemma":0.007443119,"domain_scores_codex":[0.9985439,0.000163983,0.0001436132,0.0004441228,0.0005043313,0.0002001273],"domain_scores_gemma":[0.9991341,0.0001737816,0.00004640948,0.0003148594,0.0002363918,0.00009433096],"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":[0.0002785083,0.0001655044,0.0008698479,0.001576673,0.00005768627,0.0007466942,0.0002708603,0.0004963476,0.865248,0.004047609,0.06745476,0.05878758],"study_design_scores_gemma":[0.0000736302,0.0004065791,0.005193582,0.000310277,0.0001165558,0.00102221,0.0001340248,0.001163216,0.3367819,0.002611808,0.6520869,0.00009928997],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03421418,0.01056288,0.7272022,0.002133835,0.003671239,0.008601026,0.1022308,0.01803061,0.09335324],"genre_scores_gemma":[0.03946965,0.0101956,0.475867,0.002210645,0.0006319251,0.006167647,0.295588,0.004926601,0.1649429],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05222621,"threshold_uncertainty_score":0.1747141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00868023386590525,"score_gpt":0.2757329398788738,"score_spread":0.2670527060129685,"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."}}