{"id":"W2008946437","doi":"10.1006/jfca.2002.1076","title":"Dietary Reference Intakes for the U.S. and Canada: Update on Implications for Nutrient Databases","year":2002,"lang":"en","type":"article","venue":"Journal of Food Composition and Analysis","topic":"Nutritional Studies and Diet","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Niacin; Nutrient; Dietary Reference Intake; Vitamin; Food composition data; Riboflavin; Database; Vitamin E; Retinol; Reference Daily Intake; Fortified Food; Food science; Biology; Computer science; Biochemistry; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01589639,0.001107312,0.002240537,0.01054113,0.002561287,0.003183807,0.007078436,0.001397399,0.004643631],"category_scores_gemma":[0.04184755,0.0006987852,0.002062176,0.03605945,0.0008662752,0.001951786,0.001920278,0.003544169,0.001248388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03840828,"about_ca_system_score_gemma":0.1139973,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9823968,"about_ca_topic_score_gemma":0.98327,"domain_scores_codex":[0.987936,0.001212719,0.001556599,0.0006192095,0.008235861,0.000439648],"domain_scores_gemma":[0.9265169,0.006687268,0.002791723,0.001716412,0.06040997,0.001877722],"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":[0.0006253683,0.0001700786,0.04164604,0.004961502,0.0007906497,0.0001990485,0.001176626,0.002339204,0.0006265204,0.008430678,0.6288021,0.3102322],"study_design_scores_gemma":[0.0002442599,0.00008323311,0.2086754,0.010344,0.001851157,0.0004022889,0.001690806,0.003532492,0.001397489,0.005943522,0.7655987,0.0002365031],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.03770245,0.1818339,0.04035144,0.06957336,0.008320736,0.001585742,0.5986513,0.002996762,0.05898426],"genre_scores_gemma":[0.2012497,0.2391866,0.1933725,0.02164798,0.001211161,0.002226862,0.3211615,0.000851295,0.01909248],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.03840828,"threshold_uncertainty_score":0.2786729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06946684215461815,"score_gpt":0.2990138316768119,"score_spread":0.2295469895221938,"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."}}