{"id":"W2519980925","doi":"10.1016/j.biombioe.2016.09.005","title":"Influence of moisture content and hammer mill screen size on the physical quality of barley, oat, canola and wheat straw briquettes","year":2016,"lang":"en","type":"article","venue":"Biomass and Bioenergy","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"Special Fund for Agro-scientific Research in the Public Interest; Natural Sciences and Engineering Research Council of Canada; China Scholarship Council; BioFuelNet Canada","keywords":"Briquette; Water content; Straw; Canola; Biomass (ecology); Moisture; Pulp and paper industry; Compaction; Environmental science; Hammer; Bioenergy; Agronomy; Materials science; Biofuel; Composite material; Waste management; Metallurgy; Coal","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":[0.0002965231,0.0002958014,0.0002308705,0.0002715761,0.0002236845,0.0006192066,0.000165706,0.0002515978,0.002274373],"category_scores_gemma":[0.0008987461,0.0002598914,0.0002748716,0.0002378991,0.0002735458,0.0003563411,0.0002351598,0.0003669515,0.0002536754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002778262,"about_ca_system_score_gemma":0.0002101654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002253005,"about_ca_topic_score_gemma":0.004117388,"domain_scores_codex":[0.9997956,0.00003977575,0.00002251406,0.0000434161,0.00005044768,0.0000482262],"domain_scores_gemma":[0.9990916,0.0004197152,0.0001441169,0.00003666497,0.0001487061,0.0001590906],"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":[0.003086431,0.0001310782,0.004345335,0.00008314067,0.00005046273,0.0001062606,0.0001050462,0.0004327181,0.9888306,0.00003169127,0.00005832959,0.002738905],"study_design_scores_gemma":[0.00005136855,0.001643183,0.05390344,0.00001165958,0.0001198191,0.00007982009,0.0001967346,0.001101963,0.9423351,0.00002407722,0.0005111507,0.00002155573],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992483,0.0002276456,0.0001261984,0.00001439018,0.000008457752,0.000003623511,0.00006991301,0.000007863136,0.0002936542],"genre_scores_gemma":[0.9988611,0.0001233885,0.0001873245,0.00002330823,0.00000435219,0.000003515812,0.0001017053,0.00001640031,0.0006789847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002274373,"threshold_uncertainty_score":0.007608533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0176537510815302,"score_gpt":0.217363169497428,"score_spread":0.1997094184158978,"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."}}