{"id":"W3144296094","doi":"10.3390/nu13041128","title":"Genomics and Personalized Nutrition","year":2021,"lang":"en","type":"article","venue":"Nutrients","topic":"Nutrition, Genetics, and Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Genomics; Nutrigenomics; Computational biology; Genome; Personal genomics; Biology; Functional genomics; Comparative genomics; Human genome; Bioinformatics; Genetics; Medicine; 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":[0.003131454,0.0004276359,0.000752208,0.001019034,0.0009581507,0.003379605,0.0004803112,0.003132929,0.00978176],"category_scores_gemma":[0.004731067,0.0001845618,0.00040523,0.001041024,0.005056656,0.003123595,0.00241432,0.003919093,0.00268774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001766546,"about_ca_system_score_gemma":0.00205341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001873261,"about_ca_topic_score_gemma":0.001731029,"domain_scores_codex":[0.9982457,0.0008915161,0.00005870929,0.0002572738,0.0004229126,0.0001239248],"domain_scores_gemma":[0.9980608,0.001132813,0.0001497912,0.000231373,0.0002018987,0.0002232962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001473483,0.0001454079,0.005053272,0.0009075453,0.0001396436,0.0003789661,0.001274977,0.0007601791,0.003911951,0.4606875,0.1024385,0.4241547],"study_design_scores_gemma":[0.00002699167,0.0001021656,0.004781643,0.0006312729,0.00003436862,0.000918434,0.000647451,0.0002895261,0.001329602,0.3509476,0.6402438,0.0000471614],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"review","genre_scores_codex":[0.01250442,0.3228878,0.04694436,0.433007,0.009129517,0.0001184109,0.00119895,0.0008315366,0.1733781],"genre_scores_gemma":[0.3216484,0.3560163,0.06837775,0.1716151,0.01587194,0.0003438423,0.00122524,0.0002552481,0.06464611],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.00978176,"threshold_uncertainty_score":0.03272319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008288732029943213,"score_gpt":0.2359730834229096,"score_spread":0.2276843513929664,"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."}}