{"id":"W6920399125","doi":"10.60692/dgy9c-jna79","title":"Monitoring the levels of important nutrients in the food supply","year":2013,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Obesity, Physical Activity, Diet","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Food supply; Composition (language); Food industry; Food composition data; Consumption (sociology); Food processing; Food consumption; Saturated fat","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":[0.001258843,0.0002397234,0.0002441176,0.001939244,0.0004261057,0.0007955078,0.0002913242,0.0003411049,0.001365386],"category_scores_gemma":[0.002020979,0.0001760436,0.000153664,0.002955202,0.0002375995,0.0005218658,0.000599293,0.0002630389,0.000443512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005700106,"about_ca_system_score_gemma":0.0008270607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00914157,"about_ca_topic_score_gemma":0.01597772,"domain_scores_codex":[0.9988451,0.0004148998,0.0001391443,0.000210573,0.0003313019,0.00005893641],"domain_scores_gemma":[0.9983184,0.0002699184,0.0006779739,0.0001135647,0.000505624,0.0001144719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002143058,0.0001104912,0.948076,0.0002790121,0.00009160804,0.00005257869,0.0007586752,0.0004234802,0.008967984,0.0002575172,0.001060604,0.0397077],"study_design_scores_gemma":[0.000008167456,0.0003737552,0.9857159,0.00005383925,0.000055794,0.00009672072,0.001214378,0.0008719488,0.005391998,0.0002890435,0.005913172,0.0000151992],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9760396,0.0008423327,0.004298813,0.0004629557,0.00002909399,0.000245902,0.007292421,0.00008383948,0.0107051],"genre_scores_gemma":[0.9786528,0.0008691746,0.01430137,0.00023102,0.00003086138,0.0002207667,0.00310664,0.00001337294,0.002573994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00914157,"threshold_uncertainty_score":0.01817673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0409632505794142,"score_gpt":0.2392916692903917,"score_spread":0.1983284187109775,"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."}}