{"id":"W4207077560","doi":"10.3389/fmicb.2021.798023","title":"Relative and Quantitative Rhizosphere Microbiome Profiling Results in Distinct Abundance Patterns","year":2022,"lang":"en","type":"article","venue":"Frontiers in Microbiology","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Agriculture and Agri-Food Canada; Millar College of the Bible; National Research Council Canada","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; University of Waterloo; Compute Canada; Armand-Frappier Foundation","keywords":"Rhizosphere; Relative species abundance; Abundance (ecology); Biology; Microbiome; Amplicon sequencing; Phylum; Microbial population biology; Metagenomics; Ecology; Microbial ecology; 16S ribosomal RNA; Bacteria; Gene; 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":[0.001354332,0.0006383985,0.000500882,0.001070054,0.0002105134,0.0008995839,0.0002279639,0.0006850858,0.0009119331],"category_scores_gemma":[0.001501261,0.0003255755,0.0004181096,0.001039778,0.000559959,0.0006484027,0.0005053797,0.0007091106,0.0004797813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002161327,"about_ca_system_score_gemma":0.0002273623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003908501,"about_ca_topic_score_gemma":0.0007958976,"domain_scores_codex":[0.9981604,0.0003697293,0.0001076366,0.0006588513,0.0005547199,0.0001486],"domain_scores_gemma":[0.998895,0.0004578707,0.0003003785,0.00009468554,0.0001979134,0.0000541409],"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":[0.00008815145,0.0000320154,0.005334491,0.0002050672,0.00004002532,0.00002603102,0.00006696532,0.0001567143,0.9861891,0.0001873484,0.00006973267,0.007604433],"study_design_scores_gemma":[0.00001906657,0.00048854,0.2342273,0.0000846749,0.0001776223,0.0007094578,0.000385996,0.009335768,0.746685,0.001868306,0.005943257,0.00007506875],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7938817,0.004682146,0.1910512,0.0002800856,0.0001258792,0.0001478174,0.005118638,0.0006188334,0.004093624],"genre_scores_gemma":[0.9124668,0.001784387,0.08041807,0.000288685,0.00004614767,0.0002654068,0.003075767,0.000127446,0.001527394],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001354332,"threshold_uncertainty_score":0.007162511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01051052669013611,"score_gpt":0.2148811625417775,"score_spread":0.2043706358516414,"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."}}