{"id":"W3153712018","doi":"10.1093/jn/nxab069","title":"Predicting Protein and Fat Content in Human Donor Milk Using Machine Learning","year":2021,"lang":"en","type":"article","venue":"Journal of Nutrition","topic":"Infant Nutrition and Health","field":"Nursing","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Sinai Health System; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Food science; Content (measure theory); Computer science; Chemistry; Animal science; Biology; Mathematics","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":[0.0003407211,0.0002310771,0.0003221449,0.0005573093,0.0001394907,0.0004561122,0.0001957004,0.0004252621,0.0004832126],"category_scores_gemma":[0.0007887618,0.0001120103,0.0002461031,0.0003653892,0.000134779,0.0002936384,0.0001837875,0.0003421165,0.0002390371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002717747,"about_ca_system_score_gemma":0.0002101851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002041923,"about_ca_topic_score_gemma":0.001935916,"domain_scores_codex":[0.9999182,0.00001781941,0.00000524436,0.00002679861,0.00001937009,0.00001251575],"domain_scores_gemma":[0.9997268,0.0001638307,0.00003771898,0.00001197693,0.00004573609,0.00001393003],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.005506599,0.0007126017,0.4723688,0.0002408158,0.0002953451,0.0004898738,0.0001230154,0.06044898,0.2502183,0.0004153276,0.000936207,0.2082441],"study_design_scores_gemma":[0.00004038011,0.000651388,0.1277939,0.00003233707,0.0001358198,0.0005054687,0.0002061499,0.7463395,0.1219717,0.001303375,0.0009838287,0.00003614559],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910782,0.000719999,0.007510361,0.00005084089,0.00001444768,0.00000648246,0.0002325818,0.00007064707,0.0003165252],"genre_scores_gemma":[0.9947881,0.0002440907,0.004304586,0.00002505395,0.000005192564,0.000005781338,0.0002269114,0.000008184084,0.000392137],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002041923,"threshold_uncertainty_score":0.00406009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05871351000830571,"score_gpt":0.3168570307513326,"score_spread":0.2581435207430269,"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."}}