{"id":"W2045054941","doi":"10.1007/s00253-012-4125-x","title":"Fast and accurate preparation fatty acid methyl esters by microwave-assisted derivatization in the yeast Saccharomyces cerevisiae","year":2012,"lang":"en","type":"article","venue":"Applied Microbiology and Biotechnology","topic":"Meat and Animal Product Quality","field":"Agricultural and Biological Sciences","cited_by":78,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Office of the Higher Education Commission; Fondation Chalmers; Vetenskapsrådet; Knut och Alice Wallenbergs Stiftelse","keywords":"Derivatization; Yeast; Fatty acid; Fatty acid methyl ester; Fish oil; Chemistry; Chromatography; Sample preparation; Saccharomyces cerevisiae; Polyunsaturated fatty acid; Microwave heating; Microwave; Catalysis; Organic chemistry; Biochemistry; Fish <Actinopterygii>; High-performance liquid chromatography; Biology; Biodiesel; Computer science","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":[0.0005200992,0.0005255052,0.0003191229,0.0002813696,0.0001619275,0.0002768874,0.000347108,0.0002478491,0.0005848951],"category_scores_gemma":[0.0004558038,0.0002696974,0.0002926189,0.0002155181,0.0001583054,0.0002499612,0.0003854826,0.0005767106,0.0005670675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001864527,"about_ca_system_score_gemma":0.0002801212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009882145,"about_ca_topic_score_gemma":0.001766552,"domain_scores_codex":[0.9997087,0.00004215114,0.00003024041,0.00007216689,0.0001218851,0.00002471959],"domain_scores_gemma":[0.9997646,0.00005989775,0.00003216572,0.00005523772,0.00007000686,0.00001807723],"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":[0.00007087544,0.000006109107,0.0001660446,0.00003112558,0.000007983949,0.00001805166,0.00001010636,0.00007908016,0.9919661,0.00005252599,0.00004087445,0.007551166],"study_design_scores_gemma":[0.000005030863,0.0000437669,0.0006476807,0.000001917409,0.00001164775,0.00005888851,0.000007747065,0.0004371401,0.9976451,0.000028042,0.001107985,0.000005137485],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7503103,0.006520073,0.2376012,0.0003270099,0.000228859,0.0001534829,0.001769372,0.00123177,0.001857952],"genre_scores_gemma":[0.8381843,0.003761948,0.1510435,0.00007877654,0.00004451677,0.00009345947,0.001909724,0.0001897627,0.00469396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009882145,"threshold_uncertainty_score":0.002750576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02017646699097617,"score_gpt":0.2366321082569326,"score_spread":0.2164556412659564,"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."}}