{"id":"W3097278061","doi":"10.1016/j.tifs.2020.10.035","title":"Advances in epitope mapping technologies for food protein allergens: A review","year":2020,"lang":"en","type":"review","venue":"Trends in Food Science & Technology","topic":"Food Allergy and Anaphylaxis Research","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Anhui Provincial Key Research and Development Plan; National Natural Science Foundation of China","keywords":"Epitope; Food allergy; Hypoallergenic; Allergen; Food allergens; Epitope mapping; Computational biology; Identification (biology); Allergy; Food protein; Biotechnology; Computer science; Immunology; Medicine; Biology; Antigen; Food science","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":[0.001010941,0.001128608,0.001673454,0.002261367,0.0002064971,0.001123915,0.001004563,0.001044342,0.003444925],"category_scores_gemma":[0.001090772,0.00033947,0.000847118,0.002436729,0.000344669,0.001705655,0.0007238946,0.001500374,0.001819842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004644463,"about_ca_system_score_gemma":0.001250469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009257324,"about_ca_topic_score_gemma":0.001402685,"domain_scores_codex":[0.9997354,0.00003642384,0.00003805003,0.00005198225,0.0001069918,0.00003112717],"domain_scores_gemma":[0.99936,0.0003476538,0.00009444835,0.00001682827,0.000137071,0.00004391892],"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":[0.0001050994,0.0000838796,0.0002301592,0.02736933,0.0001231097,0.0001373775,0.00003190184,0.0002843285,0.00522578,0.001613489,0.01633512,0.9484604],"study_design_scores_gemma":[0.00004043685,0.0002300815,0.001262404,0.005512712,0.0005246272,0.001042016,0.00007251722,0.0001978064,0.002747623,0.001760224,0.9865645,0.00004499168],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001318052,0.9988587,0.0002549138,0.0001356908,0.0001349058,0.00000583849,0.00003045693,0.000009061313,0.0004386097],"genre_scores_gemma":[0.0004337353,0.9986624,0.0003733976,0.0001534745,0.00009434436,0.000005750933,0.00004693442,0.000001497385,0.0002285213],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003444925,"threshold_uncertainty_score":0.0115245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09899186295615733,"score_gpt":0.4054280556490676,"score_spread":0.3064361926929103,"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."}}