{"id":"W2296152538","doi":"10.1038/srep22985","title":"Ultra–sensitive droplet digital PCR for detecting a low–prevalence somatic GNAQ mutation in Sturge–Weber syndrome","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Vascular Malformations and Hemangiomas","field":"Medicine","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Japan Science and Technology Agency; Japan Society for the Promotion of Science; Ministry of Education, Culture, Sports, Science and Technology; DNA Genotek; Japan Agency for Medical Research and Development; Hayashi Memorial Foundation for Female Natural Scientists; Takeda Science Foundation","keywords":"GNAQ; Sturge–Weber syndrome; Digital polymerase chain reaction; Somatic cell; Mutation; Germline mutation; Medicine; Genetics; Computational biology; Biology; Polymerase chain reaction; Dermatology; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001003475,0.00012932,0.0002384764,0.0003111409,0.0001744123,0.0001484094,0.00004365898,0.00006293094,0.00005369131],"category_scores_gemma":[0.0008561491,0.00009046165,0.0001651391,0.0004040713,0.0001162307,0.00056015,0.00002173068,0.00005720727,0.00004512552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001201414,"about_ca_system_score_gemma":0.0001262354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006278891,"about_ca_topic_score_gemma":0.00001724186,"domain_scores_codex":[0.9982154,0.00001862774,0.0005677044,0.0004688952,0.0004138874,0.0003155218],"domain_scores_gemma":[0.9988202,0.0001106939,0.0002451141,0.0004847757,0.0002359684,0.0001031935],"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":[0.0002729193,0.00189473,0.1497759,0.006639516,0.0005961491,0.02417592,0.01693117,0.0001411173,0.5731977,0.0003246787,0.004628655,0.2214215],"study_design_scores_gemma":[0.009037041,0.001095061,0.390226,0.01604537,0.0007483046,0.1181726,0.005395011,0.00654567,0.4213468,0.02294189,0.006234209,0.002212023],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992366,0.00004981776,0.00503748,0.0002345767,0.0009142863,0.0009321867,0.00001112348,0.00006240005,0.0003922015],"genre_scores_gemma":[0.9968629,0.000001548175,0.0005411407,0.00001962731,0.00003154164,0.00007482773,0.00004046192,0.00001718996,0.002410707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2404501,"threshold_uncertainty_score":0.3688919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01219741993103643,"score_gpt":0.2487907363347786,"score_spread":0.2365933164037422,"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."}}