{"id":"W2054081434","doi":"10.1016/j.jviromet.2012.06.021","title":"Purification and quantitation of bacteriophage M13 using desalting spin columns and digital PCR","year":2012,"lang":"en","type":"article","venue":"Journal of Virological Methods","topic":"Bacteriophages and microbial interactions","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Austrian Science Fund","keywords":"Bacteriophage; Biotinylation; Panning (audio); Digital polymerase chain reaction; Centrifugation; Biology; Chromatography; Polyethylene glycol; Titer; Microfluidics; Virus quantification; Immunomagnetic separation; Capsid; Virology; Molecular biology; Virus; Polymerase chain reaction; Materials science; Chemistry; Nanotechnology; Biochemistry; Gene; Escherichia coli","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008270547,0.00007119765,0.0001770492,0.00003570095,0.00006454554,0.00004429679,0.00005595749,0.00006599925,0.0001792695],"category_scores_gemma":[0.0002900851,0.00005486694,0.00004596696,0.00007894263,0.0001460435,0.000725819,0.00006952165,0.0001364108,0.000002320568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003415558,"about_ca_system_score_gemma":0.000003332786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001561255,"about_ca_topic_score_gemma":9.856259e-7,"domain_scores_codex":[0.9992027,0.0001681067,0.0003468746,0.00008075202,0.00007227245,0.0001293141],"domain_scores_gemma":[0.9992612,0.0001873089,0.0003872599,0.00005230202,0.00001586961,0.00009608203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00003183296,0.00006649982,0.01766255,0.000005706468,0.000008144013,9.821611e-7,0.0001974382,0.0000131571,0.9399089,0.00002950828,0.000005069787,0.04207025],"study_design_scores_gemma":[0.0001957687,0.0002728079,0.9721485,0.00002059245,0.0000410791,0.000290273,0.0001738786,0.0005489303,0.025024,0.0001629797,0.001042359,0.00007879225],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9545502,0.0002057528,0.04484775,0.00006778204,0.0001266196,0.00005355002,0.000002568773,0.000003085747,0.0001426856],"genre_scores_gemma":[0.7775409,0.00004617532,0.2223191,0.00003481872,0.00004246723,2.743974e-7,3.774813e-7,0.000003793379,0.000012147],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.954486,"threshold_uncertainty_score":0.2237409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05968762634475566,"score_gpt":0.3875759385052885,"score_spread":0.3278883121605329,"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."}}