{"id":"W2404699613","doi":"10.2172/1093743","title":"Improving Heat Recovery In Biomass-Fired Boilers","year":2013,"lang":"en","type":"report","venue":"","topic":"Thermodynamic and Exergetic Analyses of Power and Cooling Systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"FPInnovations","funders":"Oak Ridge National Laboratory; Battelle; FPInnovations; Office of Energy Efficiency; UT-Battelle; Georgia Institute of Technology; Office of Energy Efficiency and Renewable Energy; U.S. Department of Energy","keywords":"Flue gas; Dew point; Boiler (water heating); Natural gas; Water vapor; Waste management; Environmental science; Absorption heat pump; Heat recovery ventilation; Waste heat recovery unit; Waste heat; Process engineering; Petroleum engineering; Environmental engineering; Nuclear engineering; Thermodynamics; Chemistry; Engineering; Heat exchanger; Mechanical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004488921,0.0003520055,0.0005513884,0.0008880854,0.0004672111,0.0005039321,0.0005707818,0.0004136681,0.002495234],"category_scores_gemma":[0.0005319985,0.0002501038,0.0003404443,0.0005047488,0.00020695,0.0005310129,0.0003802914,0.0006065877,0.0008102573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004162016,"about_ca_system_score_gemma":0.0002916046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001978755,"about_ca_topic_score_gemma":0.004297386,"domain_scores_codex":[0.999725,0.00002414609,0.00001557737,0.00003970144,0.0001221822,0.00007329847],"domain_scores_gemma":[0.9998631,0.00003270126,0.00001437398,0.00001415711,0.00005875358,0.00001673592],"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":[0.0006250627,0.0002984751,0.002002033,0.0003496097,0.00002545662,0.0001715053,0.00006670649,0.01493047,0.9433088,0.000433137,0.0004160644,0.03737267],"study_design_scores_gemma":[0.00003856104,0.0003266947,0.003824188,0.00002182142,0.0000218274,0.0001012649,0.00003791595,0.01396952,0.9786655,0.0001438694,0.002835881,0.00001283627],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9771953,0.002329197,0.01497795,0.0001015175,0.00007058571,0.0001035737,0.0002661465,0.000355596,0.004600095],"genre_scores_gemma":[0.9907087,0.0006807719,0.005310214,0.0000236741,0.000008965644,0.00002641606,0.0002996832,0.00006251718,0.002878958],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002495234,"threshold_uncertainty_score":0.008347392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01185668326459001,"score_gpt":0.2216577232069542,"score_spread":0.2098010399423642,"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."}}