{"id":"W2781669675","doi":"10.1016/j.jaci.2017.11.007","title":"Food allergy and omics","year":2018,"lang":"en","type":"review","venue":"Journal of Allergy and Clinical Immunology","topic":"Consumer Attitudes and Food Labeling","field":"Medicine","cited_by":75,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Infection and Immunity","funders":"","keywords":"Omics; Proteomics; Genomics; Data science; Metabolomics; Food allergy; Phenomics; Epigenomics; Computer science; Precision medicine; Computational biology; Biotechnology; Allergy; Medicine; Risk analysis (engineering); Biology; Bioinformatics; Genome; Pathology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007507672,0.0003191928,0.002662148,0.000178495,0.00007572241,0.00002600886,0.0001956357,0.00090445,0.0001023478],"category_scores_gemma":[0.0004197778,0.0002206261,0.0007017894,0.00008970074,0.0005232571,0.00005452366,0.0002193236,0.001437357,0.00001384396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002840439,"about_ca_system_score_gemma":0.0003855543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004422875,"about_ca_topic_score_gemma":0.00004661236,"domain_scores_codex":[0.9971105,0.0002213666,0.001963994,0.0003036338,0.0001312708,0.0002691862],"domain_scores_gemma":[0.9974817,0.0006451946,0.001127117,0.0002832342,0.0002387373,0.0002240153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003785841,0.0002416664,0.00002326916,0.0006950385,0.03077855,0.0001128444,0.00002558393,1.288719e-8,6.303814e-7,0.0004084319,0.0004029546,0.9669324],"study_design_scores_gemma":[0.001554033,0.006171947,0.000320677,0.004435024,0.002165159,0.003707268,0.00002059705,0.000001932936,1.669081e-7,0.0001418483,0.9812918,0.000189585],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001056078,0.9970606,0.00001906688,0.0003741768,0.001082286,0.0001309891,0.00000569531,0.000009101356,0.0002620069],"genre_scores_gemma":[0.00009441434,0.9980127,0.0006633429,0.0002108229,0.0007910868,0.000001897749,0.000009119167,0.00003745105,0.0001791716],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9808888,"threshold_uncertainty_score":0.8996869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0892242434722613,"score_gpt":0.3950570857957298,"score_spread":0.3058328423234685,"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."}}