{"id":"W3134962308","doi":"10.1016/j.seta.2021.101002","title":"Simulation and techno-economic assessment of bio-methanol production from pine biomass, biochar and pyrolysis oil","year":2021,"lang":"en","type":"article","venue":"Sustainable Energy Technologies and Assessments","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":99,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hydro-Québec; Université du Québec à Trois-Rivières","funders":"","keywords":"Biochar; Biomass (ecology); Environmental science; Pyrolysis; Raw material; Bioenergy; Pulp and paper industry; Internal rate of return; Payback period; Net present value; Syngas; Waste management; Biofuel; Methanol; Production (economics); Engineering; Agronomy; Chemistry; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007749224,0.0001815531,0.0002370144,0.0002093485,0.00008244465,0.00005745732,0.0001003935,0.0002151021,0.00002221331],"category_scores_gemma":[0.00007336883,0.0001860178,0.00002395792,0.0003178896,0.000156857,0.0002412791,0.000310703,0.00009315742,2.173241e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009223806,"about_ca_system_score_gemma":0.00004746043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001755444,"about_ca_topic_score_gemma":0.00000805241,"domain_scores_codex":[0.9990543,0.00001105892,0.0002263527,0.000374513,0.0001028607,0.0002308816],"domain_scores_gemma":[0.9994666,0.00006580437,0.00008492215,0.0002586746,0.00009081456,0.0000331697],"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":[0.00001250794,0.0000564828,0.003840088,0.0006777233,0.0002828891,0.00002379739,0.00002042626,0.002002236,0.7137002,0.005829833,0.00005740015,0.2734964],"study_design_scores_gemma":[0.0003410132,0.00004686675,0.0004015225,0.00005012855,0.00005556746,0.000003063604,0.004125603,0.01338982,0.9746175,0.005411941,0.001322324,0.0002345873],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916891,0.004106369,0.003105184,0.0003337722,0.00007353712,0.00004100814,0.00001491582,0.0004740723,0.0001620808],"genre_scores_gemma":[0.9941857,0.002655858,0.002857729,0.000005048611,0.000012926,0.00003127392,0.00003646493,0.00002172956,0.0001932261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2732618,"threshold_uncertainty_score":0.7585585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005966354864631956,"score_gpt":0.2394035968119759,"score_spread":0.2334372419473439,"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."}}