{"id":"W1980804701","doi":"10.1016/j.procs.2012.04.040","title":"Measuring Gene Expression Noise in Early Drosophila Embryos: Nucleus-to-nucleus Variability","year":2012,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"British Columbia Institute of Technology","funders":"National Institute of General Medical Sciences; National Institutes of Health; National Science Foundation","keywords":"Noise (video); Computer science; Blastoderm; Biological system; Nucleus; Expression (computer science); Biology; Computational biology; Embryo; Cell biology; Artificial intelligence; Embryogenesis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005076027,0.0002882874,0.0003306807,0.0007104655,0.0001728253,0.0002880179,0.0003000646,0.000242512,0.000243778],"category_scores_gemma":[0.001491274,0.0001691625,0.0002135222,0.0004322026,0.0004066126,0.0003500282,0.000267467,0.0003797201,0.00008271836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004577174,"about_ca_system_score_gemma":0.0001467256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009942757,"about_ca_topic_score_gemma":0.0009464009,"domain_scores_codex":[0.9996376,0.00006626597,0.00001677542,0.0001096025,0.0001524272,0.00001734926],"domain_scores_gemma":[0.9992705,0.0004351602,0.0001057586,0.00006305987,0.0000963722,0.00002917031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002131284,0.00003901869,0.01635451,0.00010119,0.00005876741,0.0001562545,0.0002154986,0.02762406,0.9245775,0.001500199,0.0000828239,0.02907699],"study_design_scores_gemma":[0.00001630451,0.0002737857,0.2021456,0.00002206027,0.00006796137,0.0006256839,0.0001665163,0.3285555,0.4608872,0.006179968,0.000972789,0.00008664237],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7488724,0.0004633389,0.2494764,0.00005539787,0.00001086316,0.00001748901,0.0001803888,0.0002363051,0.0006873339],"genre_scores_gemma":[0.9675157,0.0002001069,0.03180257,0.00001717429,0.000008555904,0.00002268561,0.0001695581,0.00004706022,0.0002164378],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009942757,"threshold_uncertainty_score":0.003320992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01443056487446051,"score_gpt":0.2245146065377121,"score_spread":0.2100840416632516,"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."}}