{"id":"W2048765959","doi":"10.1016/j.biortech.2014.11.100","title":"Predicting gaseous emissions from small-scale combustion of agricultural biomass fuels","year":2014,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke; Institut de Recherche et de Développement en Agroenvironnement","funders":"Fonds de recherche du Québec – Nature et technologies; Ministère de l'Agriculture, des Pêcheries et de l'Alimentation","keywords":"Combustion; Miscanthus; Environmental science; NOx; Biomass (ecology); Bioenergy; Willow; Biomass fuels; Boiler (water heating); Biofuel; Energy crop; Environmental engineering; Waste management; Chemistry; Agronomy; Engineering; Ecology","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":[],"consensus_categories":[],"category_scores_codex":[0.00005506106,0.0001719843,0.0002349095,0.0001768575,0.0000526795,0.000008612726,0.0003603733,0.0003938248,0.00006513402],"category_scores_gemma":[0.0001378969,0.0001453961,0.00005681705,0.0004685495,0.0001612997,0.0000296499,0.0001159841,0.0001802168,0.00003182107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003573535,"about_ca_system_score_gemma":0.000005478149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002499262,"about_ca_topic_score_gemma":0.000008305961,"domain_scores_codex":[0.999127,0.00001635497,0.0002704534,0.0002247391,0.0001071249,0.0002543478],"domain_scores_gemma":[0.9993854,0.0000979801,0.00008096069,0.0003006681,0.00005745386,0.0000775316],"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":[0.000004709931,0.00002147416,0.008431709,0.0000502236,0.00002505419,8.504899e-7,0.00006698095,0.00002597715,0.9864113,0.00005285141,0.0003095498,0.004599357],"study_design_scores_gemma":[0.0002867244,0.00004389436,0.004794305,0.00006950749,0.00002967133,0.00000906141,0.0003352382,0.0003637061,0.9922245,0.0003887682,0.001282734,0.000171958],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961692,0.0003681763,0.0009521205,0.000306225,0.0001144668,0.0000966197,0.00003216452,0.00148656,0.0004744749],"genre_scores_gemma":[0.9982795,0.000009829667,0.001551092,0.00001051128,0.00005148595,0.00001188684,0.00003332501,0.00002344907,0.00002898681],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00581317,"threshold_uncertainty_score":0.5929079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005590323831773578,"score_gpt":0.1775709981747499,"score_spread":0.1719806743429763,"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."}}