{"id":"W4387358716","doi":"10.1016/j.focha.2023.100476","title":"Understanding the emerging potential of synthetic biology for food science: Achievements, applications and safety considerations","year":2023,"lang":"en","type":"article","venue":"Food Chemistry Advances","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"Consórcio Pesquisa Café; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Canada Research Chairs; Fundação de Amparo à Pesquisa do Estado de Minas Gerais; Natural Sciences and Engineering Research Council of Canada; Bill and Melinda Gates Foundation","keywords":"Synthetic biology; Biosecurity; Biosafety; Toolbox; Biotechnology; Risk analysis (engineering); Engineering ethics; Biochemical engineering; Nanotechnology; Computer science; Business; Biology; Engineering; Computational biology; Ecology","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0001550853,0.0000800565,0.00007665295,0.00002224168,0.000301495,0.00001415471,0.0001085564,0.00004069082,0.000004349418],"category_scores_gemma":[0.00007280891,0.00006857711,0.0000353679,0.0001368984,0.0002771354,0.000004445752,0.00007969105,0.00003600582,1.956249e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009306267,"about_ca_system_score_gemma":0.00004222294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":1.577104e-7,"about_ca_topic_score_gemma":0.000002389436,"domain_scores_codex":[0.9993907,0.000005344313,0.0001443829,0.0002245995,0.00006241452,0.0001725835],"domain_scores_gemma":[0.9996527,0.00003879184,0.00005174506,0.0001778674,0.00004506967,0.00003384204],"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":[0.000008763044,0.000008185958,0.00006899507,0.00006566163,0.00003123524,3.551393e-8,0.00003039113,0.002353078,0.9951134,0.00173862,0.00002636282,0.000555279],"study_design_scores_gemma":[0.0002871212,0.0001309424,0.00006606223,0.00001088329,0.00002455241,0.000007623556,0.001044254,0.0004894875,0.9814734,0.008766287,0.00758449,0.0001148777],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4149591,0.003607422,0.5785166,0.000715816,0.0001700555,0.0006284876,0.0003822419,0.00004663636,0.0009736593],"genre_scores_gemma":[0.998698,0.0003714607,0.0006519604,0.00001424728,0.00008336783,0.00008715323,0.00005453323,0.000008018244,0.0000312669],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5837389,"threshold_uncertainty_score":0.2796493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0216145427886674,"score_gpt":0.3130977460364281,"score_spread":0.2914832032477607,"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."}}