{"id":"W2190785257","doi":"10.1039/c5ib00252d","title":"Build to understand: synthetic approaches to biology","year":2015,"lang":"en","type":"review","venue":"Integrative Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Army Research Office; American Heart Association; National Institute of General Medical Sciences; Division of Mathematical Sciences; National Institutes of Health; National Science Foundation","keywords":"Synthetic biology; Biology; Computational biology; Systems biology; Task (project management); Experimental biology; Evolutionary biology; Data science; Computer science; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006167403,0.0009187367,0.002294977,0.0004568557,0.00008653447,0.00002852577,0.001001659,0.001261889,0.00004969153],"category_scores_gemma":[0.0002699582,0.0006426456,0.0007572326,0.0006400752,0.0002992796,0.000001951435,0.0006118129,0.0003554051,0.0003876396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002502737,"about_ca_system_score_gemma":0.0005839519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003391363,"about_ca_topic_score_gemma":0.0002370449,"domain_scores_codex":[0.9958152,0.001029566,0.0007374596,0.001582415,0.0001049798,0.0007303945],"domain_scores_gemma":[0.997776,0.00008303425,0.0003007096,0.001168323,0.0001951223,0.0004767655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007194863,0.0001027391,0.00002539309,0.0004037729,0.00182762,0.000004750346,0.0002140176,0.00003846227,0.000648145,0.006162998,0.01569859,0.9748015],"study_design_scores_gemma":[0.0001030697,0.0009645115,5.424918e-7,0.0004256807,0.0004459776,0.00003176899,0.0002051093,0.000003735432,0.0001858707,0.0006819293,0.9962418,0.0007099854],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001584941,0.9811334,0.01502137,0.0001773144,0.000480781,0.001136962,0.000287651,0.00003437494,0.00156965],"genre_scores_gemma":[0.001862434,0.9897105,0.002889001,0.0004151416,0.001061998,0.0004260363,0.001829143,0.0001504197,0.001655394],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9805433,"threshold_uncertainty_score":0.9996025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1633954830942551,"score_gpt":0.354589425332191,"score_spread":0.1911939422379359,"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."}}