{"id":"W2886652686","doi":"10.1016/j.energy.2018.08.058","title":"Combining petroleum coke and natural gas for efficient liquid fuels production","year":2018,"lang":"en","type":"article","venue":"Energy","topic":"Catalysts for Methane Reforming","field":"Chemical Engineering","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Department of Energy","keywords":"Petroleum coke; Natural gas; Wood gas generator; Waste management; Substitute natural gas; Greenhouse gas; Syngas; Process engineering; Environmental science; Engineering; Coke; Coal; Chemistry","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":[0.0001371088,0.0003518037,0.0003670316,0.0005038266,0.0002474725,0.00050794,0.0003408051,0.0003974296,0.002069572],"category_scores_gemma":[0.0002599643,0.0001801133,0.0001969345,0.0004260622,0.0002103661,0.001100105,0.000541663,0.0004469312,0.0007131412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004058588,"about_ca_system_score_gemma":0.0003107992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009491317,"about_ca_topic_score_gemma":0.005672882,"domain_scores_codex":[0.9998808,0.000008778175,0.000007426964,0.0000225137,0.00004373311,0.00003681748],"domain_scores_gemma":[0.9999584,0.00001142664,0.000005507081,0.000006736564,0.00001029687,0.000007761423],"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":[0.0003761494,0.0001371783,0.0004245481,0.0004233939,0.0000343527,0.0001557101,0.00004243639,0.001020348,0.9714826,0.002251162,0.000435267,0.02321685],"study_design_scores_gemma":[0.00001854057,0.0002049947,0.0005784422,0.00001248888,0.00002555914,0.00009908493,0.0000339795,0.002650579,0.9894142,0.0002678704,0.006683537,0.00001061204],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9602965,0.004931046,0.01502426,0.0003028048,0.0001902562,0.00007709019,0.0001958972,0.0002230398,0.01875916],"genre_scores_gemma":[0.9923918,0.001164624,0.002510631,0.00002212153,0.00001327256,0.00001643404,0.0001100694,0.00003244499,0.003738634],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002069572,"threshold_uncertainty_score":0.006923378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007938109169921402,"score_gpt":0.2272439001785938,"score_spread":0.2193057910086724,"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."}}