{"id":"W2953373790","doi":"10.82308/35531","title":"Biomass combustion and gasification for greenhouse carbon dioxide enrichment","year":2015,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies; BioFuelNet Canada; Ministry of Agriculture - Saskatchewan; Ministère de l'Agriculture, des Pêcheries et de l'Alimentation","keywords":"Flue gas; Syngas; Waste management; Wood gas generator; Combustion; Biomass (ecology); Environmental science; Carbon dioxide; NOx; Combustor; Pulp and paper industry; Environmental engineering; Chemistry; Coal; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0002461307,0.0003254662,0.0002192515,0.0002950592,0.0002071929,0.0003173693,0.0002363198,0.0002810578,0.001290342],"category_scores_gemma":[0.000130162,0.0001345946,0.0003021723,0.00039889,0.0001820924,0.0002188612,0.0002597019,0.0002891242,0.0003848211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003341935,"about_ca_system_score_gemma":0.0002986997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00203088,"about_ca_topic_score_gemma":0.004573732,"domain_scores_codex":[0.9997593,0.00003457982,0.000008210615,0.00005819476,0.0001092828,0.00003047238],"domain_scores_gemma":[0.9999572,0.00001071317,0.000007015834,0.000005970147,0.00001454877,0.000004579261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001075492,0.00003052763,0.001705901,0.000218582,0.00001533604,0.00007714611,0.0000184993,0.001903313,0.9698926,0.0005656327,0.00009444938,0.02537049],"study_design_scores_gemma":[0.0000163162,0.0003598115,0.008978097,0.00001975142,0.00004085994,0.0001984909,0.00004226712,0.004273844,0.9766149,0.0003131677,0.009129105,0.00001347982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9246798,0.01015339,0.05288576,0.0001154735,0.0000913973,0.0000905627,0.000313198,0.0002428375,0.01142754],"genre_scores_gemma":[0.9722482,0.003151532,0.01880653,0.00004435711,0.0000134817,0.00003000216,0.00031718,0.00003033134,0.005358452],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00203088,"threshold_uncertainty_score":0.004316628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02145821504515989,"score_gpt":0.2170620490397071,"score_spread":0.1956038339945472,"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."}}