{"id":"W4288041312","doi":"10.3390/foods11152215","title":"Development of a Canadian Food Composition Database of Gluten-Free Products","year":2022,"lang":"en","type":"article","venue":"Foods","topic":"Celiac Disease Research and Management","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Food science; Riboflavin; Nutrient; Ingredient; Food composition data; Micronutrient; Niacin; Composition (language); Dietary fiber; Legume; Food group; Chemistry; Biology; Botany; Medicine; Environmental health","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002258139,0.00005369155,0.0001210286,0.0004176525,0.00007451093,0.000002270792,0.0001213408,0.000007802344,0.0002609883],"category_scores_gemma":[0.00004259781,0.00005410285,0.00002750719,0.0004771412,0.00002385896,0.00002455055,0.0002230332,0.00006937984,0.00000300805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000132899,"about_ca_system_score_gemma":0.0008672597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003503028,"about_ca_topic_score_gemma":0.006851595,"domain_scores_codex":[0.9990895,0.00002562744,0.0001651308,0.000133439,0.0004037033,0.0001825779],"domain_scores_gemma":[0.9993086,0.000006090112,0.0000406402,0.0003686798,0.00007782114,0.0001981461],"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":[0.003872476,0.00703913,0.008239138,0.01258131,0.00297371,0.0006085548,0.006636626,0.0001198745,0.3626647,0.03167126,0.46154,0.1020532],"study_design_scores_gemma":[0.004904474,0.00238714,0.04798069,0.0002256289,0.0001869946,0.00002775125,0.001366719,0.0001406821,0.1196455,0.000138935,0.8227257,0.0002697817],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9778069,0.001106234,0.0001203733,0.004646054,0.0001524515,0.0013502,0.0007199513,0.00002694941,0.01407087],"genre_scores_gemma":[0.99101,0.0000206719,0.007996432,0.0001049875,0.00002492592,0.00007733711,0.0005649257,0.000008854115,0.0001919025],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3611857,"threshold_uncertainty_score":0.5295554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04315050807942172,"score_gpt":0.2770861628271122,"score_spread":0.2339356547476905,"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."}}