{"id":"W4413003132","doi":"10.1021/acsfoodscitech.5c00268","title":"Automatic NMR Spectral Profiling of Commercial Cow’s Milk","year":2025,"lang":"en","type":"article","venue":"ACS Food Science & Technology","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Metabolomics Innovation Centre; University of Alberta","funders":"Alberta Innovates; Canada Foundation for Innovation; National Center for Complementary and Integrative Health; Genome Canada","keywords":"Profiling (computer programming); Chemistry; Computer science; Operating system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006645338,0.0006867998,0.0005252711,0.001313021,0.0003390787,0.0006146986,0.0005342224,0.0006385804,0.002134999],"category_scores_gemma":[0.001350209,0.0003033642,0.0004049448,0.0009979422,0.0001493892,0.0004517763,0.0005658226,0.0004016282,0.0007865124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003860916,"about_ca_system_score_gemma":0.0004027626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001167931,"about_ca_topic_score_gemma":0.002165354,"domain_scores_codex":[0.9994302,0.00007004641,0.00002824528,0.000162712,0.0002630748,0.00004572352],"domain_scores_gemma":[0.9995054,0.0001430903,0.00007261043,0.0000520561,0.0002019276,0.00002491489],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000325223,0.00002740623,0.002087277,0.0001406418,0.00003373739,0.00006711137,0.00005202754,0.0005356659,0.97289,0.0001235024,0.0009448273,0.02277258],"study_design_scores_gemma":[0.00003014826,0.0001877395,0.01919301,0.00001975946,0.00005076821,0.000367162,0.00007515959,0.02950536,0.9387527,0.0002534956,0.01150381,0.00006082316],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8175153,0.001454119,0.1597078,0.0002519683,0.0001073078,0.0002509067,0.008886772,0.00769756,0.004128299],"genre_scores_gemma":[0.5874645,0.0012341,0.3909244,0.0004296454,0.00006898547,0.0004851918,0.01300025,0.00146498,0.004927946],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002134999,"threshold_uncertainty_score":0.007142305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01492553742292313,"score_gpt":0.2967459914382398,"score_spread":0.2818204540153167,"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."}}