{"id":"W3080742058","doi":"10.1016/j.foodchem.2020.127795","title":"Targeted metabolomics of anthocyanin derivatives during prolonged wine aging: Evolution, color contribution and aging prediction","year":2020,"lang":"en","type":"article","venue":"Food Chemistry","topic":"Fermentation and Sensory Analysis","field":"Agricultural and Biological Sciences","cited_by":105,"is_retracted":false,"has_abstract":false,"ca_institutions":"Brock University","funders":"China Agricultural Research System; National Natural Science Foundation of China","keywords":"Anthocyanin; Wine; Vintage; Chemistry; Food science; Wine color; Chromatography; Biochemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005740295,0.00007961268,0.0001427397,0.000004039742,0.0001207924,0.00001497228,0.00005382761,0.00005344101,0.00008571814],"category_scores_gemma":[0.0001017412,0.00004131052,0.00004184662,0.0002185957,0.00005342019,0.00008104833,0.00002730405,0.00006577505,6.475255e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000180781,"about_ca_system_score_gemma":0.000004759853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004786065,"about_ca_topic_score_gemma":0.000002875925,"domain_scores_codex":[0.9994061,0.00003042801,0.0001802249,0.0001816045,0.00009652616,0.0001051117],"domain_scores_gemma":[0.9996927,0.00002587038,0.0001133132,0.00002182503,0.00008064822,0.00006561378],"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":[0.00004687159,0.00001949997,0.01126675,0.00002691561,0.00004382533,4.517846e-7,0.0001574074,0.00003169505,0.9882948,0.000010758,0.00001678902,0.00008428313],"study_design_scores_gemma":[0.0002706185,0.00007058422,0.1144794,0.000008711278,0.00003494582,0.00000219443,0.0006828919,0.001047903,0.8831145,0.00002292988,0.0001968309,0.00006856798],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978618,0.0002280878,0.00002792553,0.001613713,0.00001070202,0.00007708369,0.00009954271,0.00004957413,0.000031587],"genre_scores_gemma":[0.9995591,0.00002142681,0.00005058251,0.00004390175,0.0001244267,0.000005438078,0.0001634046,6.361875e-7,0.00003106675],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1051803,"threshold_uncertainty_score":0.1684594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01167177540344899,"score_gpt":0.1952106192697139,"score_spread":0.1835388438662649,"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."}}