{"id":"W4293205607","doi":"10.2139/ssrn.4059740","title":"Optimization of Olefins' Yield in Fischer-Tropsch Synthesis Using Carbon Nanotubes Supported Iron Catalyst with Molybdenum and Potassium Promoters","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Catalysts for Methane Reforming","field":"Chemical Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Fischer–Tropsch process; Catalysis; Molybdenum; Yield (engineering); Potassium; Chemistry; Carbon fibers; Inorganic chemistry; Materials science; Chemical engineering; Organic chemistry; Metallurgy; Selectivity; Composite number; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0008636872,0.0001975222,0.0003281945,0.000318664,0.0001080108,0.00001325316,0.0001932139,0.00006959047,0.00002460071],"category_scores_gemma":[0.0001172994,0.0001798307,0.00006511291,0.0004434533,0.00003843559,0.0001687633,0.00009809082,0.0013322,1.23871e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001360133,"about_ca_system_score_gemma":0.0005786011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001544702,"about_ca_topic_score_gemma":0.0004644365,"domain_scores_codex":[0.9978154,0.00005941436,0.0004070538,0.0002402786,0.000376947,0.001100902],"domain_scores_gemma":[0.9994279,0.00005231244,0.000232732,0.0001805634,0.00003729859,0.00006917337],"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":[0.0002745655,0.0001396194,0.005110013,0.000107054,0.0002311044,0.00004178795,0.0006524546,0.2491714,0.7417498,0.0002364934,4.180807e-7,0.002285298],"study_design_scores_gemma":[0.002559979,0.0007944318,0.0003392778,0.0003892634,0.000560814,0.00558672,0.00849527,0.2545812,0.7252833,0.0003279305,0.0000280507,0.001053742],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970797,0.000700334,0.001847902,0.00008578491,0.00004467341,0.0001418051,0.000006741437,0.00002501475,0.00006806605],"genre_scores_gemma":[0.9993529,0.0001219621,0.00032315,0.000004807949,0.00003866566,0.00001528156,0.00001250418,0.00005508615,0.00007568599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01646648,"threshold_uncertainty_score":0.7333285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007407478763249828,"score_gpt":0.2036863629459454,"score_spread":0.1962788841826955,"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."}}