{"id":"W3193294795","doi":"10.21203/rs.2.22873/v1","title":"Temporal Dynamics of the Human Microbiome","year":2020,"lang":"en","type":"preprint","venue":"Research Square (Research Square)","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Microbiome; Dynamics (music); Human microbiome; Computer science; Biology; Psychology; Bioinformatics","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":[0.001384872,0.0002060656,0.0002475345,0.0007828496,0.0002815317,0.0009590124,0.0004252329,0.0007112581,0.003867723],"category_scores_gemma":[0.009379462,0.0001852602,0.00035597,0.0007000787,0.0005615093,0.001200799,0.0007129938,0.0005148238,0.0002967757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009713165,"about_ca_system_score_gemma":0.0003971395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007875026,"about_ca_topic_score_gemma":0.003458004,"domain_scores_codex":[0.9992781,0.0002609472,0.00002868232,0.0002635812,0.0001076045,0.00006103264],"domain_scores_gemma":[0.9973879,0.001502043,0.0005088089,0.0001730519,0.0003227742,0.0001053588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003394447,0.0001517933,0.4609861,0.0004572811,0.0003821327,0.0007348632,0.001190053,0.2906532,0.02053755,0.134855,0.005277087,0.08443552],"study_design_scores_gemma":[0.00002454001,0.0001405698,0.3030221,0.0001108337,0.00006544282,0.0007975306,0.0007768997,0.574531,0.002974,0.1073548,0.01011204,0.00009018148],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9278734,0.001715483,0.05727872,0.002198428,0.00004720979,0.0000431052,0.00231624,0.0001577315,0.008369756],"genre_scores_gemma":[0.9946732,0.0002197121,0.003679368,0.0000788157,0.00001728192,0.00001789275,0.000428892,0.00001377911,0.0008710366],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007875026,"threshold_uncertainty_score":0.01565838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1031617530927038,"score_gpt":0.4429851410354655,"score_spread":0.3398233879427617,"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."}}