{"id":"W4404695040","doi":"10.1021/acs.energyfuels.4c04169","title":"Molecular Reconstruction of Distillable Fractions of Hydrothermal Liquefaction Biocrude from Forest Biomass","year":2024,"lang":"en","type":"article","venue":"Energy & Fuels","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"Natural Resources Canada; Office of Energy Research and Development; Government of Canada","keywords":"Hydrothermal liquefaction; Biomass (ecology); Hydrothermal circulation; Liquefaction; Environmental science; Pulp and paper industry; Chemistry; Chemical engineering; Organic chemistry; Biology; Catalysis; Agronomy; 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":[0.0001905092,0.0003113072,0.0001725492,0.0003348186,0.0001279291,0.0003432088,0.0003651055,0.0003739867,0.001172833],"category_scores_gemma":[0.0003054733,0.0002726013,0.0003071612,0.0002269417,0.0002141537,0.0004318334,0.0001557507,0.0004164411,0.0002682784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003597245,"about_ca_system_score_gemma":0.0002481111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001407763,"about_ca_topic_score_gemma":0.001201695,"domain_scores_codex":[0.9999577,0.000003615034,0.000002056614,0.00001371605,0.00001535495,0.000007628572],"domain_scores_gemma":[0.9999136,0.00003124008,0.00001323033,0.00001382674,0.00002128512,0.000006728043],"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":[0.0002989223,0.00003787256,0.002375956,0.0001527511,0.00003381684,0.0003209069,0.0001317271,0.1200135,0.86094,0.002379193,0.0002178941,0.01309747],"study_design_scores_gemma":[0.00001099245,0.00006442863,0.00357683,0.000008282394,0.00002082297,0.0001023921,0.00005109806,0.6869613,0.3077842,0.0005098608,0.0008912055,0.00001860751],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8359196,0.0002591417,0.1607416,0.0001099514,0.00001441604,0.00003220894,0.0006721097,0.0007061554,0.001544726],"genre_scores_gemma":[0.920141,0.0004122287,0.07685899,0.00001958659,0.000004307309,0.00003735916,0.001005268,0.0001587381,0.001362534],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001407763,"threshold_uncertainty_score":0.003923535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005542842134711419,"score_gpt":0.1983970843834303,"score_spread":0.1928542422487189,"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."}}