{"id":"W4388967813","doi":"10.3389/fbioe.2023.1266298","title":"Epistemology of synthetic biology: a new theoretical framework based on its potential objects and objectives","year":2023,"lang":"en","type":"article","venue":"Frontiers in Bioengineering and Biotechnology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Armand Frappier Museum; Institut National de la Recherche Scientifique; Collège Montmorency","funders":"","keywords":"Synthetic biology; Hierarchy; Confusion; Set (abstract data type); Modular design; Principal (computer security); Field (mathematics); Epistemology; Computer science; Data science; Management science; Biology; Computational biology; Mathematics; Psychology; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.000178474,0.0001917737,0.000327795,0.0005271229,0.00003428895,0.000005863475,0.0001506444,0.0007478714,0.000003224771],"category_scores_gemma":[0.0001891571,0.00018058,0.00006218017,0.0004127651,0.0004648071,0.000001717983,0.0001167476,0.0002019869,0.000001172189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001153448,"about_ca_system_score_gemma":0.00003286184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002529418,"about_ca_topic_score_gemma":0.0000011095,"domain_scores_codex":[0.998893,0.00006013187,0.0002042623,0.000458469,0.00005528644,0.000328833],"domain_scores_gemma":[0.999536,0.00003213877,0.00005248984,0.0002979199,0.00001313156,0.00006833509],"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":[0.0006134389,0.000167159,0.04312234,0.0002667212,0.0005875475,0.00006867203,0.0001683727,0.02444542,0.8532218,0.02997175,0.001159325,0.04620746],"study_design_scores_gemma":[0.002500343,0.003058935,0.02158543,0.0003377199,0.0002138688,0.0001146709,0.0006741117,0.3872795,0.5505469,0.03039057,0.001942115,0.001355799],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9342943,0.003338596,0.06067624,0.00109041,0.0003443893,0.0001421196,0.00001322317,0.00007923738,0.00002150253],"genre_scores_gemma":[0.9922397,0.001132977,0.006450493,0.00003940828,0.00006009365,0.000008613173,0.00002038121,0.00002152155,0.00002678721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3628341,"threshold_uncertainty_score":0.7363839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004368073739086706,"score_gpt":0.2133370139750742,"score_spread":0.2089689402359875,"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."}}