{"id":"W4386090856","doi":"10.1021/acs.energyfuels.2c03747","title":"Upgrading of Hydrothermal Liquefaction Biocrude from Forest Residues Using Solvents and Mild Hydrotreating for Use as Co-processing Feed in a Refinery","year":2023,"lang":"en","type":"article","venue":"Energy & Fuels","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"Office of Energy Research and Development; Alberta Innovates","keywords":"Hydrothermal liquefaction; Hydrodesulfurization; Chemistry; Raw material; Deoxygenation; Toluene; Organic chemistry; Petroleum; Diesel fuel; Chemical engineering; Catalysis; Pulp and paper industry; Waste management","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":[0.0001427825,0.0002988298,0.00018968,0.0001961838,0.0001312221,0.0002519094,0.0001688357,0.0002507415,0.0008588356],"category_scores_gemma":[0.0001225107,0.0001490273,0.0002318692,0.0002059184,0.0001602201,0.0003622905,0.0001903576,0.0005047765,0.0003107533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002248404,"about_ca_system_score_gemma":0.0002008153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001252204,"about_ca_topic_score_gemma":0.003231939,"domain_scores_codex":[0.9998965,0.000007068246,0.000008009006,0.00002861829,0.00003742209,0.00002235765],"domain_scores_gemma":[0.9999419,0.000008799222,0.00001969742,0.000008305013,0.00001475725,0.000006494046],"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":[0.00001628712,0.000004426468,0.00008461334,0.00002023565,0.000001173827,0.00002641881,0.000008833762,0.00004522405,0.9989048,0.00002825798,0.0000102036,0.0008494483],"study_design_scores_gemma":[0.000001197807,0.00002975019,0.0005964386,0.000002140525,0.000002357674,0.00002461483,0.00000861327,0.000214785,0.9986688,0.000006028166,0.0004439501,0.000001431732],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9862608,0.0006392212,0.01030937,0.00005762729,0.0000134876,0.00002748467,0.0002533198,0.0001270282,0.002311533],"genre_scores_gemma":[0.9812104,0.0008833167,0.0141678,0.00003933487,0.000005748574,0.00004092938,0.0003756327,0.0000647218,0.003212156],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001252204,"threshold_uncertainty_score":0.002873123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02732642341600883,"score_gpt":0.2594340180994901,"score_spread":0.2321075946834813,"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."}}