{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003583409,0.000780765,0.0009713008,0.001275327,0.0007396128,0.004234415,0.0009723091,0.002708287,0.003186793],"category_scores_gemma":[0.002626284,0.0004494435,0.0007756264,0.0008465709,0.003396101,0.00682875,0.001679827,0.004425728,0.001107217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001483938,"about_ca_system_score_gemma":0.002058578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006983528,"about_ca_topic_score_gemma":0.0007786712,"domain_scores_codex":[0.9986898,0.0003360317,0.00007970559,0.00022047,0.0005340024,0.0001400934],"domain_scores_gemma":[0.9976966,0.001632515,0.0001278326,0.0001108195,0.0003286812,0.0001035084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001216346,0.0001198064,0.001153451,0.009617637,0.0000886335,0.0006972712,0.0008831461,0.004304002,0.06740092,0.5706152,0.01210735,0.332891],"study_design_scores_gemma":[0.00001283966,0.0002891778,0.0007169269,0.00205775,0.00005685343,0.001286842,0.0008640147,0.003441259,0.01960765,0.2613648,0.7102256,0.00007615009],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01069769,0.8521064,0.06795764,0.03082834,0.001779148,0.00005455555,0.0001683751,0.000157024,0.0362509],"genre_scores_gemma":[0.09927873,0.8420873,0.04401933,0.006187624,0.001795917,0.0001422271,0.0002557592,0.00008421378,0.006148903],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004234415,"threshold_uncertainty_score":0.01895106,"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."}}