{"id":"W1998862009","doi":"10.1021/ef5017945","title":"Pyrolysis of Woody Residue Feedstocks: Upgrading of Bio-oils from Mountain-Pine-Beetle-Killed Trees and Hog Fuel","year":2014,"lang":"en","type":"article","venue":"Energy & Fuels","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"Bioenergy Technologies Office; U.S. Department of Energy","keywords":"Pyrolysis; Liquid fuel; Pulp and paper industry; Fuel oil; Biomass (ecology); Biofuel; Yield (engineering); Pyrolysis oil; Environmental science; Waste management; Chemistry; Combustion; Materials science; Agronomy; Organic chemistry; Composite material","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001197807,0.0003311612,0.0001928327,0.0003421564,0.0001530626,0.0002550852,0.0001904927,0.0001291969,0.0008915458],"category_scores_gemma":[0.00007696982,0.0001031319,0.0002692455,0.0004405525,0.0001032291,0.0002268153,0.0001755829,0.0002675846,0.0001874171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001880393,"about_ca_system_score_gemma":0.0001949793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001550265,"about_ca_topic_score_gemma":0.003142294,"domain_scores_codex":[0.9998977,0.00000657695,0.000006518801,0.00001926014,0.00004170181,0.00002814553],"domain_scores_gemma":[0.9999568,0.000003860631,0.000009106267,0.000003892298,0.00001099553,0.00001540851],"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":[0.0001620805,0.00002619235,0.001001065,0.00004479963,0.000007882434,0.00008349527,0.00001709755,0.0002196621,0.9963939,0.0000237036,0.0000070577,0.002013159],"study_design_scores_gemma":[0.00000623025,0.0003316886,0.009137841,0.000004195665,0.00001599793,0.00006893822,0.00003995379,0.0004124677,0.9894357,0.00001026152,0.0005334225,0.000003310925],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985273,0.0001246291,0.0006439783,0.000002712386,0.000002615364,0.00001155686,0.0001745807,0.00001279623,0.0004997955],"genre_scores_gemma":[0.9968335,0.0001984407,0.001465515,0.000004994964,0.000001253852,0.000009449694,0.0004972622,0.00001186653,0.0009777463],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001550265,"threshold_uncertainty_score":0.003082454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005192650777354459,"score_gpt":0.1867966443453676,"score_spread":0.1816039935680132,"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."}}