{"id":"W2782570775","doi":"10.21307/jofnem-2017-082","title":"Modeling Host-Microbiome Interactions in <i>Caenorhabditis elegans</i>","year":2017,"lang":"en","type":"article","venue":"Journal of Nematology","topic":"Genetics, Aging, and Longevity in Model Organisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Queen's University","funders":"","keywords":"Microbiome; Caenorhabditis elegans; Biology; Host (biology); Computational biology; Model organism; Gut microbiome; Evolutionary biology; Genetics; Ecology; Gene","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":[0.000222536,0.0003866153,0.0002863532,0.0002629213,0.0002920746,0.0004169142,0.0005989824,0.0005911932,0.0007561888],"category_scores_gemma":[0.0004708087,0.0002304204,0.0003693783,0.000137483,0.0003930448,0.0003044478,0.0003616069,0.0003046938,0.00006850801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006935321,"about_ca_system_score_gemma":0.0009627531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03072418,"about_ca_topic_score_gemma":0.02114203,"domain_scores_codex":[0.9999282,0.00001814431,0.00000280636,0.00001940965,0.00001631286,0.00001496605],"domain_scores_gemma":[0.9998145,0.00008082124,0.00004767075,0.000007811801,0.00002188358,0.00002738929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003470392,0.00005485967,0.002982696,0.00003764734,0.00002913411,0.00006827957,0.00001148299,0.9818897,0.01021931,0.002691806,0.0001718532,0.001808491],"study_design_scores_gemma":[0.00001182937,0.00003911751,0.00136512,0.000004311361,0.00001339082,0.00001305063,0.00001088676,0.9966353,0.0009760428,0.0006319144,0.0002931162,0.000006010655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.948808,0.0005268298,0.04111924,0.0002558846,0.00003434303,0.00004286935,0.0003176931,0.0001345475,0.008760426],"genre_scores_gemma":[0.9884065,0.0002859134,0.00951626,0.00003401518,0.000006560853,0.00003742408,0.00008445632,0.00001870327,0.001610126],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03072418,"threshold_uncertainty_score":0.06109065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01720137825151207,"score_gpt":0.2884321343506037,"score_spread":0.2712307560990916,"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."}}