{"id":"W4385069035","doi":"10.3390/molecules28145536","title":"Co-Fermentation of Agri-Food Residues Using a Co-Culture of Yeasts as a New Bioprocess to Produce 2-Phenylethanol","year":2023,"lang":"en","type":"article","venue":"Molecules","topic":"Fermentation and Sensory Analysis","field":"Agricultural and Biological Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre National en Électrochimie et en Technologies Environnementales; York University; Institut National de la Recherche Scientifique; Collège Shawinigan; Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Ministère de l'Éducation et de l'Enseignement supérieur; Instituto Potosino de Investigación Científica y Tecnológica; University of Warwick; York University; Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke","keywords":"Bioprocess; Food science; Kluyveromyces marxianus; Kluyveromyces lactis; Chemistry; Fermentation; Bioreactor; Biotechnology; Yeast; Pulp and paper industry; Biology; Saccharomyces cerevisiae; Biochemistry; Engineering","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":[0.0000859776,0.00009651426,0.0001651309,0.00004341377,0.00007134818,0.00002236639,0.0001324039,0.00004982966,0.0001466113],"category_scores_gemma":[0.00008787904,0.0000435836,0.00007411445,0.000853988,0.00003621238,0.00006260358,0.00001778247,0.00003468428,0.00004562216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001129239,"about_ca_system_score_gemma":0.00001852642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002449841,"about_ca_topic_score_gemma":0.00012229,"domain_scores_codex":[0.9991088,0.00005541321,0.0002203799,0.0002170364,0.0002607426,0.0001376574],"domain_scores_gemma":[0.9996294,0.00001757798,0.0001171147,0.00004998994,0.00009470805,0.00009125628],"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":[0.00003894089,0.00003520747,0.001088233,0.00001994202,0.00002880292,0.000001761255,0.001520431,0.000115445,0.9931144,0.0000594754,0.0009000706,0.003077322],"study_design_scores_gemma":[0.0001247384,0.0003206811,0.04593515,0.00004137495,0.00002834557,0.000002039502,0.003322888,0.00004852573,0.9493268,0.0002973944,0.0004378532,0.0001142749],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998475,0.00003470122,0.00001267356,0.000701572,0.00001917437,0.000181661,0.00005606638,0.00003923024,0.0004799543],"genre_scores_gemma":[0.9982455,0.00001539734,0.0002665374,0.0002296081,0.00004884312,0.000005013017,0.0001315369,0.000001214828,0.001056304],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04484691,"threshold_uncertainty_score":0.1777288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04542897870298578,"score_gpt":0.3102744105021799,"score_spread":0.2648454317991941,"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."}}