{"id":"W2054171853","doi":"10.1111/j.1539-6924.2009.01322.x","title":"Quantitative Risk Assessment Relating to Adventitious Presence of Allergens in Food: A Probabilistic Model Applied to Peanut in Chocolate","year":2009,"lang":"en","type":"article","venue":"Risk Analysis","topic":"Food Allergy and Anaphylaxis Research","field":"Medicine","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada","funders":"","keywords":"Peanut oil; Peanut allergy; Consumption (sociology); Population; Risk assessment; Food allergens; Peanut butter; Food allergy; Environmental health; Toxicology; Food science; Medicine; Biotechnology; Biology; Allergy; Computer science; Immunology","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":[0.0009460881,0.0001722316,0.0006300208,0.001363381,0.00006746386,0.00001598662,0.0001701048,0.00007856524,0.00004634335],"category_scores_gemma":[0.0007718009,0.0001600386,0.0002119387,0.00371788,0.00003157459,0.00006329094,0.0000678959,0.000452728,0.00001393203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001795368,"about_ca_system_score_gemma":0.0001362388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001054214,"about_ca_topic_score_gemma":0.01251142,"domain_scores_codex":[0.9977822,0.0001758614,0.0006134147,0.0004980816,0.0005389947,0.0003915012],"domain_scores_gemma":[0.998873,0.0001722806,0.0001682076,0.0004079131,0.0001667714,0.0002118126],"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":[0.0004402727,0.0005926518,0.03322776,0.00004047466,0.0006013815,0.00001679012,0.002609182,0.955118,0.001693813,0.002200339,0.00005676618,0.003402569],"study_design_scores_gemma":[0.0009435749,0.00133311,0.3226261,0.0001235087,0.0001408613,3.01816e-7,0.0006189116,0.6702885,0.0001234142,0.003584269,0.00002982153,0.000187657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9804528,0.0001139246,0.01452661,0.0004231733,0.000006771614,0.0009494735,0.00003392264,0.00001950333,0.003473843],"genre_scores_gemma":[0.9830257,0.0001721609,0.01638023,0.00005364632,0.00001107691,0.000104966,0.00002020291,0.0000111668,0.0002207982],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2893983,"threshold_uncertainty_score":0.6981667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02421081356095905,"score_gpt":0.3467690905981113,"score_spread":0.3225582770371523,"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."}}