{"id":"W3111916324","doi":"10.1016/j.jviromet.2020.114045","title":"Treatments of porcine fecal samples affect high-throughput virome sequencing results","year":2020,"lang":"en","type":"article","venue":"Journal of Virological Methods","topic":"Bacteriophages and microbial interactions","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dawson College; Université de Montréal; Cegep de Trois-Rivieres; Cégep Garneau; Agriculture and Agri-Food Canada; Cegep de Thetford","funders":"Agriculture and Agri-Food Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Biology; Human virome; Feces; Pyrosequencing; DNA sequencing; Affect (linguistics); Throughput; Computational biology; Metagenomics; Genetics; Microbiology; Gene","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001145273,0.0005725343,0.0003447114,0.0002809214,0.0005811697,0.001255824,0.0002792096,0.0009473907,0.002683391],"category_scores_gemma":[0.001808364,0.0003719825,0.0005477103,0.0003146374,0.0005125038,0.00031715,0.0003610174,0.0007273357,0.0008787266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002493566,"about_ca_system_score_gemma":0.0003550444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001309036,"about_ca_topic_score_gemma":0.004157497,"domain_scores_codex":[0.9984737,0.0004227152,0.0001126809,0.0003763863,0.0003680313,0.0002464258],"domain_scores_gemma":[0.9991693,0.0004391684,0.00009206024,0.00006330449,0.0001851547,0.00005100805],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002612637,0.00003389579,0.002435908,0.00008891558,0.00003394121,0.00002842991,0.00006851554,0.00008080567,0.9939971,0.00002611579,0.0001797078,0.002765485],"study_design_scores_gemma":[0.00001154844,0.0003667065,0.03646461,0.00003098221,0.00006695686,0.0001599765,0.0002213422,0.001095358,0.9577785,0.00009737039,0.003683627,0.00002308842],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9662119,0.00185775,0.02308791,0.0006449405,0.0005484025,0.0001699578,0.002635203,0.0002825973,0.00456147],"genre_scores_gemma":[0.9497027,0.001028573,0.0366044,0.001770034,0.00006589561,0.0002597981,0.005199483,0.0003870773,0.004981964],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9988548,"threshold_uncertainty_score":0.008976877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1044843543922435,"score_gpt":0.378362627850332,"score_spread":0.2738782734580885,"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."}}