{"id":"W4220883236","doi":"10.3390/fuels3010010","title":"Torrefaction and Densification of Wood Sawdust for Bioenergy Applications","year":2022,"lang":"en","type":"article","venue":"Fuels","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; Saskatchewan Polytechnic; Global Institute for Water Security; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; BioFuelNet Canada","keywords":"Torrefaction; Sawdust; Pellets; Pulp and paper industry; Heat of combustion; Biochar; Materials science; Pyrolysis; Bioenergy; Waste management; Pelletizing; Furfural; Raw material; Steam explosion; Briquette; Pellet; Straw; Coal; Biofuel; Composite material; Chemistry; Organic chemistry","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":[0.0001022446,0.0003324965,0.0001875764,0.0002146846,0.00009122975,0.0002177156,0.0001424022,0.0001649578,0.0006393897],"category_scores_gemma":[0.00007341485,0.0001256187,0.000252327,0.0002343592,0.0001112623,0.0002830969,0.0001159681,0.0003001252,0.0001381504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001621591,"about_ca_system_score_gemma":0.0001308465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007655796,"about_ca_topic_score_gemma":0.003284554,"domain_scores_codex":[0.9999166,0.000007315122,0.000006250323,0.00001820347,0.00003137717,0.00002036543],"domain_scores_gemma":[0.9999727,0.000004090693,0.000009042579,0.000003057174,0.000007191396,0.00000392404],"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":[0.00006498236,0.00002362113,0.0004203366,0.0001519605,0.00001191382,0.000105232,0.00002310647,0.0004643059,0.992007,0.000145868,0.00002174269,0.006559917],"study_design_scores_gemma":[0.000004385775,0.0001842265,0.004252881,0.00001099776,0.00001862898,0.0001105324,0.00005855429,0.001149487,0.9916795,0.00005347301,0.002472007,0.000005290416],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880918,0.00390169,0.006211995,0.00002949994,0.00002951482,0.0000208452,0.0001035588,0.0000264068,0.00158463],"genre_scores_gemma":[0.9950442,0.001582113,0.00207781,0.00001471829,0.000006778687,0.000007271678,0.0001467204,0.000008873511,0.001111419],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007655796,"threshold_uncertainty_score":0.002138913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01058638680887867,"score_gpt":0.2073752338601465,"score_spread":0.1967888470512678,"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."}}