{"id":"W3184881209","doi":"10.1016/j.biortech.2021.125652","title":"Enhanced biogas production from Lantana camara via bioaugmentation of cellulolytic bacteria","year":2021,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Anaerobic Digestion and Biogas Production","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"Biotechnology and Biological Sciences Research Council; Department of Science and Technology, Ministry of Science and Technology, India; Department of Biotechnology, Ministry of Science and Technology, India","keywords":"Bioaugmentation; Cellulase; Lantana camara; Biogas; Biomass (ecology); Food science; Bacteria; Chemistry; Biology; Pulp and paper industry; Biotechnology; Cellulose; Agronomy; Botany; Microorganism; Biochemistry; Ecology","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":[0.0000491028,0.0001307562,0.0001712796,0.0002231649,0.00003537086,0.000009175691,0.00009950408,0.0001994618,0.0001740103],"category_scores_gemma":[0.00003739228,0.0001372999,0.00004035714,0.0005771617,0.0001098808,0.00005922983,0.0000325477,0.0001117698,0.00006867615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006522743,"about_ca_system_score_gemma":0.000015064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000261114,"about_ca_topic_score_gemma":0.00003206744,"domain_scores_codex":[0.9992094,0.00001781602,0.0002415047,0.0002727278,0.00009394029,0.000164588],"domain_scores_gemma":[0.9994977,0.000007628694,0.00006738997,0.0003214361,0.00007726036,0.00002863365],"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":[0.000009671149,0.0000355119,0.0004937038,0.000009788473,0.00003632071,0.000004562844,0.00006878594,0.0001273182,0.9893315,0.001246053,0.0003238174,0.008312979],"study_design_scores_gemma":[0.0001892414,0.00003447779,0.002223935,0.00002535305,0.00002777715,0.00001761298,0.0003160852,0.0001064167,0.9908152,0.0004190465,0.00569253,0.0001323867],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991472,0.0004837906,0.005505178,0.0007296852,0.0006875415,0.000118391,0.00001593393,0.0006393452,0.000348127],"genre_scores_gemma":[0.9974652,0.0001649671,0.001876499,0.00001437801,0.0001217023,0.0000114282,0.0001327785,0.00002065352,0.0001924288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008180592,"threshold_uncertainty_score":0.5598927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005616271534421586,"score_gpt":0.1892497148508175,"score_spread":0.1836334433163959,"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."}}