{"id":"W2746406260","doi":"10.1016/j.fuproc.2017.07.011","title":"Development of an integrated system for electricity and hydrogen production from coal and water utilizing a novel chemical hydrogen storage technology","year":2017,"lang":"en","type":"article","venue":"Fuel Processing Technology","topic":"Ammonia Synthesis and Nitrogen Reduction","field":"Chemical Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ontario Institute of Technology","funders":"Natural Sciences and Engineering Research Council of Canada; Atomic Energy of Canada Limited","keywords":"Hydrogen production; Integrated gasification combined cycle; Syngas; Hydrogen; Coal; Coal gasification; Ammonia production; Waste management; Exergy; Process engineering; Environmental science; Exergy efficiency; Combined cycle; Wood gas generator; Electricity generation; Chemistry; Ammonia; Turbine; Engineering; Power (physics)","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":[0.0001960391,0.0002209478,0.000392374,0.000341541,0.0003242728,0.00003405411,0.0002928892,0.0005130286,0.00000132424],"category_scores_gemma":[0.0001943619,0.0001844546,0.00002512025,0.0001461596,0.0002991177,0.0001933371,0.0001727717,0.000250547,8.749381e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001088319,"about_ca_system_score_gemma":0.00005572568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001840687,"about_ca_topic_score_gemma":0.000006907564,"domain_scores_codex":[0.998646,0.000006177143,0.0003681329,0.0005419377,0.0001005011,0.0003372132],"domain_scores_gemma":[0.999229,0.00001073575,0.0002289281,0.0003580732,0.0001217538,0.00005155493],"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":[0.00006366867,0.0000618632,0.0002169817,0.0002840484,0.00005322533,0.000001204887,0.0001958255,0.000005956769,0.948692,0.0001842735,4.880389e-7,0.05024046],"study_design_scores_gemma":[0.0004074716,0.00003415071,0.0000191241,0.0001669239,0.00005607784,0.00008452994,0.0007031116,0.02036367,0.9770918,0.0004634328,0.0004006943,0.0002089995],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881065,0.0007052541,0.01015244,0.0002361982,0.00004386702,0.0002756146,0.00000979658,0.0004573337,0.00001294198],"genre_scores_gemma":[0.9459274,0.000004725377,0.05383456,0.000001704431,0.00005313131,0.0001107006,0.00002144581,0.00003681865,0.000009538364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05003146,"threshold_uncertainty_score":0.7521842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01720070111126948,"score_gpt":0.237060422046941,"score_spread":0.2198597209356715,"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."}}