{"id":"W2994389370","doi":"10.1016/j.btre.2019.e00407","title":"Optimization of carotenoids production by Rhodotorula mucilaginosa (MTCC-1403) using agro-industrial waste in bioreactor: A statistical approach","year":2019,"lang":"en","type":"article","venue":"Biotechnology Reports","topic":"Antioxidant Activity and Oxidative Stress","field":"Medicine","cited_by":168,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Infection and Immunity","keywords":"Carotenoid; Food science; Fermentation; Aeration; Husk; Chemistry; Biomass (ecology); Bioreactor; Raw material; Response surface methodology; Compost; Pulp and paper industry; Botany; Biology; Agronomy; Chromatography; Organic chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003751963,0.000200119,0.0005454368,0.0003677467,0.00003587082,0.000007292648,0.00006429177,0.0007592964,0.00003491229],"category_scores_gemma":[0.0004583795,0.000185565,0.00005915597,0.0005123126,0.0003086099,0.0001388078,0.00006921119,0.0005155968,0.000001709731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001381281,"about_ca_system_score_gemma":0.0001647842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002555619,"about_ca_topic_score_gemma":0.00000363457,"domain_scores_codex":[0.998198,0.00007836564,0.0005658803,0.0005966504,0.0002706829,0.0002904409],"domain_scores_gemma":[0.9988936,0.00002831614,0.0004223042,0.0005060892,0.00009375311,0.0000559508],"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":[0.0002346054,0.0006948282,0.1385344,0.0001450343,0.00007872941,0.0001555298,0.0000859081,0.001401719,0.8560526,0.0002183539,0.0003605815,0.002037656],"study_design_scores_gemma":[0.001740779,0.0004768181,0.003919004,0.0002692083,0.0001516431,0.001470914,0.0007082167,0.01066936,0.979623,0.00005364394,0.0005698909,0.0003475164],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9731764,0.00008917256,0.02461568,0.0002867714,0.0004033388,0.001002313,0.00002378558,0.00009575255,0.0003068254],"genre_scores_gemma":[0.9877433,0.00002917431,0.01179768,0.000009959373,0.00008825689,0.0000119726,0.000155777,0.00002333902,0.0001405297],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1346154,"threshold_uncertainty_score":0.7567122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02420161736100664,"score_gpt":0.2607049547373583,"score_spread":0.2365033373763517,"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."}}