{"id":"W2221100080","doi":"10.1021/acssynbio.5b00156","title":"Measurements of Gene Expression at Steady State Improve the Predictability of Part Assembly","year":2015,"lang":"en","type":"article","venue":"ACS Synthetic Biology","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China; Petroleum Technology Alliance Canada","keywords":"Predictability; Computational biology; Gene expression; Gene; Biology; Expression (computer science); Genetics; State (computer science); Steady state (chemistry); Evolutionary biology; Computer science; Mathematics; Statistics; Chemistry; Algorithm","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004420014,0.0004015252,0.0005504267,0.0003262954,0.0002346176,0.0007333244,0.0005000986,0.0004122057,0.0006649437],"category_scores_gemma":[0.002191449,0.0003078951,0.0002416949,0.000401027,0.0006517578,0.0009585996,0.0005550375,0.001243701,0.000258385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005624316,"about_ca_system_score_gemma":0.0003647128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006122843,"about_ca_topic_score_gemma":0.0007099339,"domain_scores_codex":[0.9996939,0.0000417233,0.00001700428,0.0001195406,0.00009422383,0.00003356246],"domain_scores_gemma":[0.9988437,0.0007005853,0.0001352877,0.0001499642,0.0001203329,0.00005009145],"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":[0.0000879879,0.00003228693,0.005205033,0.0000700192,0.00001048227,0.00005172034,0.0001024866,0.007650615,0.9715737,0.002546425,0.0001063645,0.01256275],"study_design_scores_gemma":[0.000007217619,0.0001993359,0.02517897,0.00001414913,0.00002107296,0.00007880412,0.00007796317,0.1428937,0.8264496,0.00386551,0.001169852,0.00004381298],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7158316,0.0008565563,0.2783648,0.0002802893,0.00005223428,0.00002749069,0.0004049489,0.0009239175,0.003258219],"genre_scores_gemma":[0.9855838,0.000219136,0.0136657,0.0000368801,0.00001056312,0.00002453335,0.0001160934,0.00004250228,0.000300788],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007333244,"threshold_uncertainty_score":0.004080713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03420009760792908,"score_gpt":0.2877547436320977,"score_spread":0.2535546460241687,"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."}}