{"id":"W3203343559","doi":"10.23880/ppej-16000271","title":"Technologies for Tar Removal from Biomass-Derived Syngas","year":2021,"lang":"en","type":"article","venue":"Petroleum & Petrochemical Engineering Journal","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"National Research Council Canada","keywords":"Syngas; tar (computing); Commercialization; Renewable energy; Biomass (ecology); Waste management; Environmental science; Environmentally friendly; Fossil fuel; Process engineering; Engineering; Chemistry; Business; Computer science; Organic chemistry; Catalysis","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001207043,0.0004349115,0.0005047324,0.0001947956,0.0001013897,0.0001642602,0.000559116,0.0004951313,0.0001752113],"category_scores_gemma":[0.0007968631,0.0004524102,0.000322869,0.0003551223,0.0000632954,0.0002219992,0.000134074,0.001025755,0.00003473117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003385271,"about_ca_system_score_gemma":0.00007111142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001425989,"about_ca_topic_score_gemma":6.041894e-7,"domain_scores_codex":[0.9979336,0.00001067583,0.0005441475,0.0004092355,0.0003651167,0.000737233],"domain_scores_gemma":[0.9987856,0.0003037681,0.0000811401,0.0003782967,0.0001972574,0.000253995],"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":[0.00002803722,0.00003171841,0.00003258322,0.0001292985,0.0002082388,0.0001674503,0.00002801501,0.001150194,0.9951919,0.00005520793,0.001590972,0.001386438],"study_design_scores_gemma":[0.0009337466,0.00002814416,0.00002386745,0.0001329022,0.00006986661,0.0006298704,0.0001382496,0.01361872,0.9619124,0.000495712,0.02150484,0.0005116759],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9102669,0.006174575,0.07940675,0.0007496778,0.001076411,0.00007302026,0.00008203553,0.001991502,0.0001791072],"genre_scores_gemma":[0.9476808,0.0003151851,0.05122282,0.00003800373,0.0004468934,0.00003191632,0.00007400139,0.0001242585,0.0000661254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03741388,"threshold_uncertainty_score":0.9997928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006468110785757224,"score_gpt":0.1915509239720304,"score_spread":0.1850828131862731,"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."}}