{"id":"W4240136836","doi":"10.1515/iupac.79.1304","title":"Food Intolerance","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Child Nutrition and Feeding Issues","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Hazard; Toxicology; Computer science; Chemistry; Biology; Philosophy; Linguistics; Organic chemistry","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":[0.0008565289,0.001578266,0.001425834,0.003922484,0.0007204916,0.002421858,0.002075854,0.001591943,0.1073291],"category_scores_gemma":[0.009542773,0.0003924929,0.001834259,0.006371825,0.0002568979,0.001613379,0.001707811,0.001365801,0.09288386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001174995,"about_ca_system_score_gemma":0.001967479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01763539,"about_ca_topic_score_gemma":0.03071426,"domain_scores_codex":[0.998688,0.0001963399,0.0002706342,0.0004065112,0.0002771671,0.000161299],"domain_scores_gemma":[0.9966619,0.0008145458,0.0006088382,0.0006183806,0.001082305,0.0002140976],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002832028,0.00004409943,0.006755724,0.002502762,0.0001117775,0.00006493909,0.00004280741,0.0002010803,0.00009728145,0.0007307661,0.9730642,0.01610121],"study_design_scores_gemma":[0.0001783186,0.00002846282,0.01543972,0.001254321,0.00009367582,0.0001739545,0.0001340362,0.0001790068,0.0001597891,0.001012936,0.9813146,0.00003114294],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003739157,0.000276487,0.000062267,0.00008468481,0.00004464679,0.0000250923,0.9962623,0.0001049799,0.002765721],"genre_scores_gemma":[0.001025344,0.0002876688,0.0002588878,0.0001948132,0.00002052134,0.0001152095,0.9957132,0.00003795778,0.002346424],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1073291,"threshold_uncertainty_score":0.3590515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02066208154837518,"score_gpt":0.4098847776588221,"score_spread":0.389222696110447,"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."}}