{"id":"W2986985985","doi":"10.1016/j.biortech.2019.122404","title":"Cost, energy and GHG emission assessment for microbial biodiesel production through valorization of municipal sludge and crude glycerol","year":2019,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":49,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biodiesel; Biodiesel production; Biomass (ecology); Environmental science; Pulp and paper industry; Waste management; Biofuel; Diesel fuel; Glycerol; Bioenergy; Chemistry; Agronomy; Engineering; Biology","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":[0.0001075799,0.000138922,0.0001785686,0.0001056434,0.00005678511,0.00000789175,0.00008723392,0.0002908094,0.000002267729],"category_scores_gemma":[0.00006189827,0.0001286899,0.00003144507,0.000134249,0.000135299,0.000005337713,0.0001035622,0.00005820861,2.9369e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001120934,"about_ca_system_score_gemma":0.00001721469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002809124,"about_ca_topic_score_gemma":0.000006555264,"domain_scores_codex":[0.9991814,0.00001794335,0.0001855559,0.0003967719,0.00004807052,0.0001702413],"domain_scores_gemma":[0.9995124,0.000003203609,0.0001044043,0.0002790559,0.0000768176,0.00002406886],"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":[0.00009484179,0.00003731593,0.001320321,0.00006589647,0.00002795297,7.105517e-8,0.00004900429,0.00002508391,0.990928,0.0003704495,0.0005338594,0.006547216],"study_design_scores_gemma":[0.0005823859,0.0003348512,0.0004247735,0.00002258936,0.00002417306,0.00002591482,0.0001019189,0.0000819972,0.8506416,0.00007830314,0.1475491,0.0001324015],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922701,0.001061146,0.005408045,0.0005276362,0.000267751,0.0003716286,0.00002187999,0.00004249822,0.0000292773],"genre_scores_gemma":[0.9932085,0.0006315639,0.005376829,0.00003236777,0.0001876395,0.00003543542,0.00009903303,0.0000193636,0.0004092224],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1470152,"threshold_uncertainty_score":0.5247821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01041622306911376,"score_gpt":0.2518475453202462,"score_spread":0.2414313222511324,"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."}}