{"id":"W4389009126","doi":"10.1016/j.biortech.2023.130102","title":"Environmental assessment of Rhodosporidium toruloides-1588 based oil production using wood hydrolysate and crude glycerol","year":2023,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique; York University","funders":"","keywords":"Biodiesel; Ecotoxicity; Biofuel; Hydrolysate; Biomass (ecology); Environmental science; Raw material; Biodiesel production; Pulp and paper industry; Bioenergy; Food science; Fossil fuel; Chemistry; Life-cycle assessment; Environmental chemistry; Agronomy; Biotechnology; Biology; Production (economics); Organic chemistry; Hydrolysis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002060163,0.0004771161,0.0002246497,0.0002636678,0.0002252851,0.0004219864,0.0003298095,0.0004348831,0.0005835624],"category_scores_gemma":[0.0001790437,0.0001370273,0.0002788223,0.0002550324,0.0001410775,0.0002442631,0.0003269862,0.0003258114,0.0002651982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002853144,"about_ca_system_score_gemma":0.0003314104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003700435,"about_ca_topic_score_gemma":0.005665512,"domain_scores_codex":[0.9997172,0.00004694238,0.00002453489,0.00005462201,0.0001112179,0.00004554861],"domain_scores_gemma":[0.9999092,0.00001723661,0.00001377682,0.000005364194,0.00003907716,0.00001531431],"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":[0.0004139286,0.0001346412,0.001525887,0.0000550591,0.000007735151,0.0001089964,0.00001468218,0.0007176429,0.9944572,0.00001811725,0.00002856453,0.002517472],"study_design_scores_gemma":[0.00001388723,0.0007851426,0.008501912,0.000007557414,0.00002013313,0.00003763093,0.00009788003,0.001283669,0.9888425,0.00001450483,0.0003886156,0.000006492928],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975987,0.0001411862,0.000603774,0.00002514139,0.000006147043,0.0000295205,0.0005249823,0.00002152799,0.001048963],"genre_scores_gemma":[0.9965476,0.0002891282,0.001179361,0.00001954127,0.000001823247,0.00003564853,0.0008013461,0.00001103273,0.00111454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003700435,"threshold_uncertainty_score":0.007357776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007374735706035965,"score_gpt":0.2340807525312484,"score_spread":0.2267060168252124,"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."}}