{"id":"W2955721554","doi":"10.1186/s12896-019-0529-3","title":"Genome-wide sequencing and metabolic annotation of Pythium irregulare CBS 494.86: understanding Eicosapentaenoic acid production","year":2019,"lang":"en","type":"article","venue":"BMC Biotechnology","topic":"Polyamine Metabolism and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Regional Development Fund; Agriculture and Agri-Food Canada; Fundação de Amparo à Pesquisa do Estado de São Paulo; Fundação para a Ciência e a Tecnologia; Universidade do Minho; European Commission","keywords":"Biology; Eicosapentaenoic acid; Gene; Genome; Metabolic pathway; Biochemistry; Metabolic engineering; Biotechnology; Computational biology; Fatty acid; Polyunsaturated fatty acid","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":[0.0005811002,0.001072529,0.0008979984,0.00146953,0.0007043409,0.001308267,0.0004672349,0.0006884093,0.001103536],"category_scores_gemma":[0.0009748181,0.0003201194,0.0012452,0.002895923,0.0002737436,0.0004822258,0.0009124351,0.0009291025,0.001121868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005402888,"about_ca_system_score_gemma":0.001337511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005174156,"about_ca_topic_score_gemma":0.003501096,"domain_scores_codex":[0.9995058,0.00003913172,0.00004892617,0.0001880742,0.0001356786,0.0000823951],"domain_scores_gemma":[0.9995477,0.00007795389,0.00009144387,0.00005858416,0.0001496076,0.00007475655],"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":[0.001155084,0.0001466143,0.01070639,0.001224642,0.0001045099,0.0007511525,0.000461959,0.002221961,0.9546093,0.0001917394,0.00169496,0.02673184],"study_design_scores_gemma":[0.0003516487,0.001143452,0.3637116,0.0008427541,0.001782172,0.004163539,0.0025595,0.03233688,0.4690265,0.001635836,0.1221562,0.0002899868],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8898357,0.005289405,0.01483878,0.0006169853,0.0001046612,0.0002540622,0.08368951,0.001329792,0.004041117],"genre_scores_gemma":[0.7035536,0.004968112,0.05725782,0.0002206491,0.00006154577,0.0003770972,0.2294638,0.0006784452,0.003418776],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005174156,"threshold_uncertainty_score":0.01028806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01968409014517228,"score_gpt":0.2343111311357536,"score_spread":0.2146270409905813,"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."}}