{"id":"W2913485659","doi":"10.1002/masy.201800026","title":"Polymer Additives as Cold Flow Improvers for Palm Oil Methyl Esters","year":2019,"lang":"en","type":"article","venue":"Macromolecular Symposia","topic":"Biodiesel Production and Applications","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universidade Federal do Paraná; Réseau Provincial de Recherche en Adaptation-Réadaptation; Petrobras","keywords":"Biodiesel; Diesel fuel; Pour point; Raw material; Acrylate; Polymer; Chemistry; Methyl methacrylate; Biofuel; Chemical engineering; Palm oil; Materials science; Organic chemistry; Methyl acrylate; Pulp and paper industry; Copolymer; Waste management; Food science; Catalysis","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001902291,0.0006830248,0.0002651122,0.0005105406,0.0001652313,0.0003099978,0.0002476235,0.0003738078,0.001548852],"category_scores_gemma":[0.0002610693,0.0002339011,0.0004200011,0.0002093067,0.0001594738,0.0005335593,0.0002742099,0.0006265583,0.000757473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001522029,"about_ca_system_score_gemma":0.0001097916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001836313,"about_ca_topic_score_gemma":0.0004611573,"domain_scores_codex":[0.9997961,0.00003096833,0.00001729862,0.00004672214,0.00007273871,0.0000362864],"domain_scores_gemma":[0.9998318,0.00002505744,0.00006665302,0.00001293762,0.00003989926,0.00002358636],"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":[0.00007307614,0.00005130713,0.00009045142,0.0001209534,0.000006550261,0.00003954712,0.00001187219,0.0001350985,0.9953086,0.000088306,0.0000277677,0.004046538],"study_design_scores_gemma":[0.000002834313,0.0001830241,0.0003003952,0.000008474068,0.00001277498,0.00002984909,0.000004648137,0.0002660261,0.9974106,0.000008012732,0.001770412,0.000003066804],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9636595,0.007015727,0.02213183,0.0001375752,0.0001439101,0.0001573224,0.0001849375,0.0004357371,0.006133441],"genre_scores_gemma":[0.9648879,0.00545076,0.02301205,0.0001056368,0.00006052538,0.00008777614,0.0001852225,0.00009953875,0.006110582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001548852,"threshold_uncertainty_score":0.005181432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003408476187966324,"score_gpt":0.1985578611460499,"score_spread":0.1951493849580835,"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."}}