{"id":"W1617121735","doi":"10.1016/j.jneb.2015.04.187","title":"A Comparison of the Nutrient Content Between Gluten-Free Foods to Matched Gluten-Containing Products","year":2015,"lang":"en","type":"article","venue":"Journal of Nutrition Education and Behavior","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Science Foundation","keywords":"Micronutrient; Food science; Niacin; Riboflavin; Fortification; Gluten free; Nutrient; Food composition data; Gluten; Serving size; Chemistry; Multivitamin; Vitamin; Micronutrient deficiency; Biochemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000452978,0.0002115394,0.0002876477,0.0008680803,0.0003190925,0.00035366,0.00019174,0.0004102536,0.002384855],"category_scores_gemma":[0.001312518,0.0001615883,0.0002689027,0.0005195977,0.0002630682,0.0004019928,0.0004067425,0.0002841669,0.000293145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001705461,"about_ca_system_score_gemma":0.0001318802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001671005,"about_ca_topic_score_gemma":0.001778626,"domain_scores_codex":[0.9997748,0.00005705819,0.0000242684,0.00005085277,0.00006428889,0.00002877248],"domain_scores_gemma":[0.9993613,0.0003080219,0.00008073301,0.00003456573,0.0001020617,0.0001131608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.2500954,0.007717573,0.3598737,0.0009459854,0.001077671,0.0007513585,0.002178516,0.000328506,0.3126256,0.0006743733,0.0006405825,0.06309061],"study_design_scores_gemma":[0.0005014296,0.0245984,0.9455088,0.00002992013,0.0003943504,0.0005202972,0.001549737,0.0006146604,0.02412913,0.0003043782,0.001821895,0.00002710225],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992449,0.0001528686,0.00007290871,0.000009270964,0.00001204811,0.000008080929,0.00009577602,0.000002395105,0.000401788],"genre_scores_gemma":[0.9987424,0.0001340146,0.0002795129,0.00003285127,0.000005951021,0.000009366906,0.0002228192,0.000003128655,0.0005700667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002384855,"threshold_uncertainty_score":0.007978082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3962273214497513,"score_gpt":0.508729070848981,"score_spread":0.1125017493992297,"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."}}