{"id":"W1590774234","doi":"10.5772/20032","title":"Conversion of Non-Homogeneous Biomass to Ultraclean Syngas and Catalytic Conversion to Ethanol","year":2011,"lang":"en","type":"book-chapter","venue":"InTech eBooks","topic":"Catalysis for Biomass Conversion","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"CRB Innovations; Natural Sciences and Engineering Research Council of Canada; Ministère des Ressources Naturelles et de la Faune; Enerkem","keywords":"Syngas; Homogeneous; Biomass (ecology); Ethanol; Catalysis; Syngas to gasoline plus; Chemistry; Chemical engineering; Pulp and paper industry; Organic chemistry; Engineering; Biology; Physics; Ecology; Thermodynamics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0001998093,0.00026322,0.0001969704,0.0004407651,0.0001389479,0.0003333086,0.0003275709,0.0002250365,0.001185763],"category_scores_gemma":[0.0001412704,0.0001800618,0.0004179733,0.0004915351,0.0001635582,0.0004524312,0.0003822106,0.0005684586,0.0005484534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003441687,"about_ca_system_score_gemma":0.0002436516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001147574,"about_ca_topic_score_gemma":0.003737896,"domain_scores_codex":[0.9998409,0.00001263446,0.000009123073,0.0000266829,0.00007782721,0.00003277206],"domain_scores_gemma":[0.9999712,0.000004168871,0.000004943664,0.000005059761,0.00001024858,0.000004494052],"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":[0.000146244,0.0002384789,0.0008572497,0.0004553956,0.00003872768,0.0003152956,0.00008714626,0.002284888,0.947253,0.00370804,0.0004959386,0.04411959],"study_design_scores_gemma":[0.00001126776,0.0001782429,0.001364551,0.00002638026,0.00001286963,0.0001525261,0.00006973438,0.002898941,0.9827844,0.0005379913,0.01195159,0.0000114962],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9311934,0.007594613,0.03216949,0.0002650477,0.0002774567,0.0001441138,0.0004104731,0.0001544888,0.02779097],"genre_scores_gemma":[0.9787897,0.003065997,0.008401977,0.00007918085,0.000009608906,0.00004353346,0.0002794986,0.00002155848,0.009308957],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001185763,"threshold_uncertainty_score":0.003966808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01183701741053907,"score_gpt":0.2023711196772484,"score_spread":0.1905341022667094,"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."}}