{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001566455,0.0005072704,0.0003886157,0.002050829,0.0001690249,0.0004408226,0.0005730051,0.000812933,0.0008230543],"category_scores_gemma":[0.002558264,0.0003182853,0.0002695907,0.0004723843,0.0005743119,0.0004130975,0.0003139673,0.0005021318,0.0002822369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002977361,"about_ca_system_score_gemma":0.0002275179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003630536,"about_ca_topic_score_gemma":0.0005827131,"domain_scores_codex":[0.9986293,0.0004412781,0.0001272799,0.0003011348,0.0004247818,0.00007632201],"domain_scores_gemma":[0.9989249,0.0006613029,0.0001274475,0.00007590336,0.0001244458,0.00008602962],"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":[0.0002721889,0.0001450733,0.05698923,0.0002214907,0.00003754977,0.002149764,0.0003145761,0.0006011118,0.8791192,0.0006470926,0.0003175866,0.05918514],"study_design_scores_gemma":[0.0001328157,0.002256518,0.1244492,0.0001084285,0.0002018916,0.03487899,0.0005935606,0.04962445,0.7786447,0.002115317,0.006878467,0.0001156619],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8734882,0.002357002,0.1212495,0.0002188832,0.0001204762,0.0002368398,0.0002416355,0.0004653184,0.001622121],"genre_scores_gemma":[0.8824472,0.0006759503,0.1153892,0.000172919,0.00003398426,0.0001510355,0.0002341366,0.00003787883,0.0008577724],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002050829,"threshold_uncertainty_score":0.00828433,"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."}}