{"id":"W4362541130","doi":"10.1158/1538-7445.am2023-3050","title":"Abstract 3050: Quality control samples for future population-based microbiome studies","year":2023,"lang":"en","type":"article","venue":"Cancer Research","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Jaccard index; UniFrac; Microbiome; Intraclass correlation; Biology; Statistics; Population; Metagenomics; Diversity index; Principal component analysis; Alpha diversity; Mathematics; Genetics; Ecology; Medicine; Reproducibility; Species diversity; Cluster analysis; Bacteria; 16S ribosomal RNA","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":[0.08649684,0.001406887,0.001462989,0.00324277,0.002009484,0.004082252,0.003134632,0.00249159,0.005088715],"category_scores_gemma":[0.08090979,0.0007926471,0.001384682,0.003131718,0.002582471,0.001663583,0.002392605,0.001927448,0.002920155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001688993,"about_ca_system_score_gemma":0.003643241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00385633,"about_ca_topic_score_gemma":0.003244367,"domain_scores_codex":[0.9429161,0.02785823,0.005765964,0.004285407,0.01814548,0.001028813],"domain_scores_gemma":[0.9084545,0.01746369,0.01300763,0.01916861,0.04047804,0.001427432],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00425911,0.002478311,0.3849491,0.003587199,0.001001858,0.0004323887,0.00231433,0.006516839,0.2573792,0.007423726,0.02422001,0.3054379],"study_design_scores_gemma":[0.0008133211,0.005566861,0.547247,0.002406506,0.001087684,0.001722337,0.001264451,0.01783114,0.2910925,0.007836012,0.122757,0.0003751427],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2600422,0.004137433,0.6916377,0.002656007,0.001099434,0.01095277,0.0171231,0.003401847,0.008949559],"genre_scores_gemma":[0.3340847,0.001079234,0.6234116,0.002040513,0.0005729724,0.01021912,0.02433958,0.001131932,0.003120369],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08649684,"threshold_uncertainty_score":0.4574445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1978097231551609,"score_gpt":0.5209525222921364,"score_spread":0.3231427991369755,"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."}}