{"id":"W4280506439","doi":"10.1136/bmjopen-2021-057989","title":"Association between gut MIcrobiota, GROWth and Diet in peripubertal children from the TARGet Kids! cohort (The MiGrowD) study: protocol for studying gut microbiota at a community-based primary healthcare setting","year":2022,"lang":"en","type":"article","venue":"BMJ Open","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"Canadian Institutes of Health Research; Alexander S. Onassis Public Benefit Foundation; University of Toronto","keywords":"Gut flora; Anthropometry; Medicine; Cohort study; Prospective cohort study; Cohort; Health care; Gerontology; Public health; Body mass index; Physiology; Pediatrics; Demography; Internal medicine; Immunology; Nursing","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.008296953,0.002110511,0.002962578,0.001836397,0.002883442,0.001388377,0.002416259,0.002403473,0.01917841],"category_scores_gemma":[0.007423209,0.001772645,0.001565663,0.001886907,0.0009962569,0.001122174,0.001758855,0.001604948,0.004596804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00253373,"about_ca_system_score_gemma":0.009208235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01444294,"about_ca_topic_score_gemma":0.02105222,"domain_scores_codex":[0.9965575,0.001441068,0.0006250631,0.0005533276,0.0003438577,0.000479247],"domain_scores_gemma":[0.9962518,0.0004539871,0.0006791413,0.0006517904,0.001335064,0.0006283528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.1146309,0.01656942,0.3555012,0.02888348,0.001389765,0.00382123,0.01307346,0.002762894,0.01376109,0.008162265,0.3532935,0.08815083],"study_design_scores_gemma":[0.03076181,0.02350375,0.7021586,0.008153454,0.0007902064,0.001278682,0.006054,0.00339295,0.003553366,0.003126469,0.216779,0.0004477761],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.06900068,0.0009540746,0.005378775,0.0007399184,0.0004106348,0.8613755,0.05562703,0.0002630279,0.006250431],"genre_scores_gemma":[0.01939489,0.0003631574,0.005293479,0.0002533272,0.0000632063,0.964355,0.008547569,0.00002204837,0.001707296],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.01917841,"threshold_uncertainty_score":0.0641582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04540651128515822,"score_gpt":0.3638531345491362,"score_spread":0.318446623263978,"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."}}