{"id":"W2573896704","doi":"10.1002/cjce.22792","title":"Comminution of biogenic materials","year":2017,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Biofuel production and bioconversion","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Comminution; Renewable energy; Environmental science; Biomass (ecology); Mill; Raw material; Process engineering; Renewable resource; Specific energy; Process (computing); Pulp and paper industry; Materials science; Computer science; Engineering; Mechanical engineering; Metallurgy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001638239,0.0003930521,0.0002592408,0.0004785661,0.0004080875,0.0004458124,0.0002279563,0.0002349516,0.003513154],"category_scores_gemma":[0.0002077056,0.0001043187,0.0003190469,0.0004796782,0.0001777304,0.0003114271,0.0003450757,0.0003758192,0.0004430235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003316879,"about_ca_system_score_gemma":0.000162548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008240415,"about_ca_topic_score_gemma":0.002596633,"domain_scores_codex":[0.9997957,0.00002006927,0.00001374138,0.00004937141,0.00007667145,0.0000445489],"domain_scores_gemma":[0.9998415,0.00004186195,0.00004088473,0.0000238793,0.00003337742,0.00001856094],"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":[0.0001122324,0.00005923094,0.001070048,0.0001951765,0.00001581346,0.0001827616,0.00004342807,0.000650316,0.9855134,0.000200127,0.00007880248,0.01187864],"study_design_scores_gemma":[0.000003747803,0.0001556774,0.003875704,0.00001486155,0.000008801457,0.00007895223,0.000033207,0.0009171013,0.992169,0.00007812773,0.002661631,0.000003175382],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9886126,0.001463375,0.003980774,0.00003655303,0.00004368413,0.00004080734,0.0001760949,0.0000609056,0.005585266],"genre_scores_gemma":[0.9941175,0.000351915,0.001929632,0.0000367713,0.000005670868,0.00001101218,0.0001609944,0.00002594864,0.003360481],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003513154,"threshold_uncertainty_score":0.01175267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0114101742932972,"score_gpt":0.1838973549743823,"score_spread":0.1724871806810851,"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."}}