{"id":"W2075556947","doi":"10.1002/cjce.20558","title":"An expert model for estimation of the performance of direct dimethyl ether synthesis from synthesis gas","year":2011,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Catalysis and Oxidation Reactions","field":"Chemical Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dimethyl ether; Backpropagation; Gradient descent; Selectivity; Yield (engineering); Artificial neural network; Chemistry; Syngas; Approximation error; Conjugate gradient method; Ether; Mathematics; Analytical Chemistry (journal); Algorithm; Physics; Artificial intelligence; Computer science; Thermodynamics; Chromatography; Organic chemistry; Methanol; Hydrogen; Catalysis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002284234,0.0001100266,0.0002489013,0.00008196447,0.00003956935,0.000008682116,0.0003704871,0.00007856912,0.00006163323],"category_scores_gemma":[0.0006236034,0.00007332582,0.0001881389,0.0001332502,0.00005515806,0.0001295974,0.000009776134,0.0001592615,4.615696e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009023101,"about_ca_system_score_gemma":0.0001006053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001335292,"about_ca_topic_score_gemma":0.00006816137,"domain_scores_codex":[0.9992343,0.00001015246,0.0003791268,0.00007669943,0.0001468322,0.0001528525],"domain_scores_gemma":[0.9989438,0.0003437143,0.0001890294,0.00026777,0.0001069424,0.000148711],"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":[0.00001543431,0.00001462076,0.00003909615,0.00002381871,0.00008532902,1.715405e-7,0.0008195403,0.3293642,0.6671126,0.0001474911,0.00002242643,0.002355236],"study_design_scores_gemma":[0.00003666794,0.000003664435,0.00004638106,0.00008008724,0.00005664804,0.000001801442,0.000009775626,0.4777074,0.5219778,0.0000229549,0.00001143494,0.00004539221],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9852901,0.0001109429,0.01422584,0.00009387136,0.00008008055,0.00006604746,0.00004254698,0.000008661968,0.00008198289],"genre_scores_gemma":[0.9935528,0.000003736924,0.00632355,0.00001083078,0.00006148879,0.00001357565,0.000001665104,0.0000242186,0.000008117162],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1483432,"threshold_uncertainty_score":0.299014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01898285504081577,"score_gpt":0.2075535536789038,"score_spread":0.188570698638088,"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."}}