{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002017911,0.0001437226,0.0003262845,0.0013627,0.0002263618,0.00002454898,0.001191925,0.0002061897,0.0001468165],"category_scores_gemma":[0.0005428509,0.0001364845,0.00006078963,0.006767216,0.001604737,0.0001088681,0.0002735363,0.0003039426,0.000009189162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001406592,"about_ca_system_score_gemma":0.0003298435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001380483,"about_ca_topic_score_gemma":0.00001595644,"domain_scores_codex":[0.9985555,0.000004632489,0.0003232618,0.0003827968,0.0002676426,0.0004661171],"domain_scores_gemma":[0.9990772,0.00006059513,0.0001389442,0.0005643059,0.0001185654,0.00004040506],"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":[0.000005940868,0.0001213431,0.04067466,0.00008164277,0.00005184147,0.000002548747,0.0000497671,0.000006254117,0.9125188,0.04181774,0.00007812502,0.004591354],"study_design_scores_gemma":[0.0002258221,0.00009238529,0.0009425287,0.00002745148,0.00006892999,0.000008100756,0.0006869433,0.0004163736,0.9898874,0.007414332,0.0001120961,0.0001176698],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9796657,0.0004765677,0.000473544,0.001016128,0.00006785785,0.00006230627,0.000006152905,0.0002961102,0.01793564],"genre_scores_gemma":[0.997862,0.00001536318,0.001812773,0.00006407997,0.00001724017,0.00001552586,0.000001614641,0.000006297305,0.0002051529],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07736858,"threshold_uncertainty_score":0.5912722,"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."}}