{"id":"W1525739002","doi":"10.1002/jsfa.5920","title":"Screening of agro‐industrial wastes for citric acid bioproduction by <i>Aspergillus niger</i><scp>NRRL</scp> 2001 through solid state fermentation","year":2012,"lang":"en","type":"article","venue":"Journal of the Science of Food and Agriculture","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut de Recherche et de Développement en Agroenvironnement; Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Solid-state fermentation; Citric acid; Biomass (ecology); Raw material; Pomace; Pulp and paper industry; Food science; Fermentation; Aspergillus niger; Substrate (aquarium); Chemistry; Waste management; Bioproduction; Biotechnology; Agronomy; Biology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004357375,0.0007686763,0.0004894931,0.000413707,0.000170232,0.0007890475,0.0003772353,0.0004589164,0.000490565],"category_scores_gemma":[0.0003842468,0.0002054907,0.0006356352,0.0006372954,0.0001729455,0.000380521,0.0004265946,0.0004815221,0.000347573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003176287,"about_ca_system_score_gemma":0.0003099178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009963879,"about_ca_topic_score_gemma":0.001548868,"domain_scores_codex":[0.9994211,0.0001059742,0.00009710481,0.00009711527,0.0002211545,0.00005760687],"domain_scores_gemma":[0.9996984,0.00007706819,0.00007517866,0.00003503359,0.00008125078,0.0000330487],"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":[0.00006952116,0.0001129976,0.0008445524,0.00009052994,0.00001177433,0.00007504007,0.00001380258,0.0002475379,0.9960386,0.00001674366,0.00001588694,0.002462924],"study_design_scores_gemma":[0.000007533771,0.0006406167,0.004567141,0.00001699274,0.0000318343,0.0001975136,0.00004516169,0.0005257659,0.9934233,0.00001532586,0.000521756,0.000006924],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933375,0.00126817,0.003227031,0.00007915733,0.00001196313,0.0001124954,0.0005786076,0.00006243928,0.001322643],"genre_scores_gemma":[0.9879182,0.001344979,0.008569089,0.00003423151,0.000005038124,0.00006134567,0.001161376,0.00002063412,0.0008851942],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009963879,"threshold_uncertainty_score":0.002304614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.013801872093708,"score_gpt":0.2305981825583714,"score_spread":0.2167963104646634,"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."}}