{"id":"W2052239099","doi":"10.1016/j.fuproc.2014.03.007","title":"Optimization of glycerol ketalization to produce solketal as biodiesel additive in a continuous reactor with subcritical acetone using Purolite® PD206 as catalyst","year":2014,"lang":"en","type":"article","venue":"Fuel Processing Technology","topic":"Catalysis for Biomass Conversion","field":"Engineering","cited_by":75,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Isfahan University of Technology","keywords":"Acetone; Yield (engineering); Chemistry; Catalysis; Glycerol; Biodiesel; Central composite design; Volumetric flow rate; Organic chemistry; Nuclear chemistry; Response surface methodology; Chromatography; Materials science; Thermodynamics; Metallurgy","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001754302,0.0002536348,0.0004349808,0.0009593975,0.0000532513,0.00003898,0.0002499531,0.0003021155,0.00001472738],"category_scores_gemma":[0.0005196524,0.0002568859,0.00003686848,0.001685534,0.0002328635,0.0003087577,0.0001047556,0.0002000529,0.00002074473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001713521,"about_ca_system_score_gemma":0.00007743677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007420007,"about_ca_topic_score_gemma":0.0000485055,"domain_scores_codex":[0.9984888,0.00002621492,0.0003991184,0.0004521147,0.0002438579,0.0003898597],"domain_scores_gemma":[0.9991255,0.00002952307,0.0001181814,0.0003696809,0.0002851615,0.00007188709],"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":[0.001256298,0.0007624425,0.0110219,0.00306906,0.0003461036,0.000130822,0.003640302,0.1153105,0.8060061,0.002105994,0.0002352407,0.05611524],"study_design_scores_gemma":[0.00199575,0.0007492837,0.000315323,0.0007194378,0.0002074398,0.0003136199,0.001044924,0.4381256,0.5537685,0.000714876,0.001155437,0.0008897744],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9151983,0.000255192,0.08240189,0.0003411467,0.00008082351,0.0004798352,0.00002000759,0.0006327633,0.0005901061],"genre_scores_gemma":[0.9872731,0.000008840833,0.01239415,0.00003125547,0.0000345701,0.00004604455,0.0001366202,0.00006030798,0.00001512579],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3228151,"threshold_uncertainty_score":0.9999883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005281624394462608,"score_gpt":0.2187371646145713,"score_spread":0.2134555402201087,"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."}}