{"id":"W4398173169","doi":"10.21203/rs.3.rs-4355889/v1","title":"Quantifying the intra- and inter-species community interaction in a microbiome by dynamic covariance mapping","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto; Université de Sherbrooke; Université de Montréal","funders":"","keywords":"Microbiome; Biology; Evolutionary biology; Microbial population biology; Community; Competition (biology); Ecology; Computational biology; Genetics; Ecosystem; Bacteria","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":[0.0006512,0.000399001,0.0003258012,0.0008215228,0.0003483772,0.0005973644,0.000391843,0.0004071791,0.001170149],"category_scores_gemma":[0.002051427,0.0001837026,0.0005188655,0.0009609066,0.000389576,0.0006764602,0.0008883283,0.0006555867,0.0003238734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003839843,"about_ca_system_score_gemma":0.0004853258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002739841,"about_ca_topic_score_gemma":0.003997084,"domain_scores_codex":[0.9996393,0.0000534497,0.00001883597,0.0001430898,0.0001064025,0.0000389027],"domain_scores_gemma":[0.9992328,0.0003090448,0.0002107442,0.00007550988,0.000116913,0.00005508465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003575266,0.0002895441,0.1395612,0.0005904564,0.0003772691,0.0002825914,0.0005497831,0.09533679,0.5568347,0.01123797,0.003641713,0.1909405],"study_design_scores_gemma":[0.0000153326,0.0001814443,0.1408488,0.00004288793,0.00009284906,0.000321983,0.0002935607,0.7832528,0.05694164,0.01173285,0.006155624,0.0001202157],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5213475,0.0005390645,0.471856,0.0002914177,0.0000605879,0.00006344775,0.002114629,0.0008061056,0.002921257],"genre_scores_gemma":[0.8578696,0.0003958221,0.1382437,0.0001282884,0.00004676229,0.0001276519,0.00202853,0.0001391111,0.00102066],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002739841,"threshold_uncertainty_score":0.005447805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09729621549472059,"score_gpt":0.418764835832364,"score_spread":0.3214686203376433,"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."}}