{"id":"W4292938003","doi":"10.3407/rpn.v5i2.6745","title":"Aplicaciones de la proteómica en la investigación fitoquímica","year":2022,"lang":"es","type":"article","venue":"Revista Productos Naturales","topic":"Plant biochemistry and biosynthesis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mica; Biology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001224732,0.0004743886,0.0004080948,0.00007559072,0.0004664498,0.0002322478,0.0008650484,0.000447303,0.00009608466],"category_scores_gemma":[0.00132689,0.0004551262,0.000262469,0.0002925537,0.0004539393,0.00001112862,0.0007661392,0.0008842992,0.00001520929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009910644,"about_ca_system_score_gemma":0.0004532521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008054239,"about_ca_topic_score_gemma":3.577457e-7,"domain_scores_codex":[0.996105,0.00154322,0.0004146448,0.001058501,0.0003395867,0.0005390873],"domain_scores_gemma":[0.9983929,0.0002258531,0.0002709833,0.0008492577,0.00007213299,0.0001888343],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002378782,0.000238394,0.00155002,0.0007648834,0.0001825395,0.00005764455,0.00007984801,0.00001110953,0.9734669,0.001400795,0.01870311,0.003306843],"study_design_scores_gemma":[0.0001632705,0.00009167836,0.0007696053,0.00008766259,0.0000766485,0.0005463841,0.00006099278,0.00001301098,0.4551515,0.00005015285,0.5425969,0.0003921581],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9670795,0.02432793,0.000005232635,0.00522096,0.0001079284,0.0007133757,0.0007634308,0.00006630929,0.001715319],"genre_scores_gemma":[0.991188,0.00305719,0.0007058883,0.0003096496,0.001023014,0.0001650512,0.0006821619,0.00005783178,0.002811186],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5238938,"threshold_uncertainty_score":0.9997901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004142229060280092,"score_gpt":0.2375691622756486,"score_spread":0.2334269332153685,"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."}}