{"id":"W4385145787","doi":"10.1007/s13399-023-04625-8","title":"Torrefaction severity influence on the nutrient composition of biomass","year":2023,"lang":"en","type":"article","venue":"Biomass Conversion and Biorefinery","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Abdul Latif Jameel Water and Food Systems Lab, Massachusetts Institute of Technology; Tata Trusts; Mitacs; Office of Energy Efficiency and Renewable Energy; Pacific Institute for Climate Solutions","keywords":"Torrefaction; Nutrient; Biomass (ecology); Husk; Carbon fibers; Amendment; Chemistry; Composition (language); Environmental chemistry; Agronomy; Pulp and paper industry; Botany; Materials science; Organic chemistry; Biology; Pyrolysis","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":[0.0001480576,0.0001691331,0.0001565349,0.0001833032,0.00009711015,0.00002228381,0.0001531896,0.0001319703,0.00006405624],"category_scores_gemma":[0.00002341237,0.0001197656,0.00006174681,0.0006578567,0.000151642,0.0001094662,0.00007604503,0.00009057535,0.0001206007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004675299,"about_ca_system_score_gemma":0.0000114074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000213701,"about_ca_topic_score_gemma":5.069195e-7,"domain_scores_codex":[0.9991155,0.00002986326,0.0002149709,0.0002044165,0.0002397825,0.0001954426],"domain_scores_gemma":[0.9994364,0.0001571744,0.00006115495,0.0002065412,0.00005820348,0.0000805278],"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":[0.00005279909,0.00002240433,0.0008850577,0.0001957745,0.00002460934,0.000003967176,0.00004666953,0.000003323942,0.9931314,0.0002729586,0.004456495,0.0009045252],"study_design_scores_gemma":[0.0003130268,0.00005182649,0.008597839,0.00006536981,0.00001357388,0.000003721156,0.0001184472,0.0007916111,0.9859681,0.0000848197,0.003827102,0.0001645601],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980907,0.00008425055,0.00001916496,0.0006920721,0.0003152064,0.0001377775,0.00004113081,0.0003796769,0.0002400652],"genre_scores_gemma":[0.9995946,0.0001613623,0.00001622267,0.0001022521,0.00002422805,0.00000968503,0.00003735609,0.00001464372,0.00003964933],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007712781,"threshold_uncertainty_score":0.4883899,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01215732644241538,"score_gpt":0.2074033043929819,"score_spread":0.1952459779505665,"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."}}