{"id":"W2135623916","doi":"10.1371/journal.pone.0134802","title":"Methods for Improving Human Gut Microbiome Data by Reducing Variability through Sample Processing and Storage of Stool","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":318,"is_retracted":false,"has_abstract":true,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Crohn's and Colitis Canada; Canadian Association of Gastroenterology","keywords":"Microbiome; Feces; Human microbiome; DNA extraction; Biology; Food science; Microbiology; Bioinformatics; Polymerase chain reaction; Genetics","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":[],"consensus_categories":[],"category_scores_codex":[0.0192298,0.001666386,0.001433934,0.002892525,0.001556089,0.002349386,0.002171864,0.001670777,0.004915427],"category_scores_gemma":[0.0313951,0.001319114,0.001536529,0.003162741,0.001491573,0.00200336,0.002276267,0.002346838,0.004058659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006622532,"about_ca_system_score_gemma":0.00191117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001288783,"about_ca_topic_score_gemma":0.003247163,"domain_scores_codex":[0.9879305,0.004459532,0.001394285,0.002323841,0.003546625,0.0003451361],"domain_scores_gemma":[0.9791728,0.005556182,0.0037991,0.005304047,0.005760051,0.0004077235],"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":[0.0009901841,0.0004485351,0.02814336,0.002946649,0.0005467813,0.0003616024,0.001163082,0.002705459,0.7340811,0.003463477,0.0104461,0.2147037],"study_design_scores_gemma":[0.0002313117,0.001790374,0.07813197,0.001266734,0.001175962,0.001739686,0.0007700089,0.0150884,0.770506,0.008908513,0.1199541,0.0004369447],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0630485,0.0064331,0.9137021,0.002162221,0.001294157,0.001776367,0.005365758,0.003763019,0.002454949],"genre_scores_gemma":[0.08866195,0.003660011,0.8907019,0.001130682,0.0004772944,0.004019903,0.007918851,0.001251921,0.002177316],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0192298,"threshold_uncertainty_score":0.1016981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1293696954180726,"score_gpt":0.3795882359212663,"score_spread":0.2502185405031938,"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."}}