{"id":"W1995517774","doi":"10.1371/journal.pone.0025400","title":"Transcriptional Profiling of Endocrine Cerebro-Osteodysplasia Using Microarray and Next-Generation Sequencing","year":2011,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Genomic variations and chromosomal abnormalities","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Children’s Health Research Institute; Lawson Health Research Institute; University of Toronto; Western University; Robarts Clinical Trials","funders":"Canadian Institutes of Health Research; Ontario Genomics; Ontario Genomics Institute; Genome Canada; Heart and Stroke Foundation of Canada","keywords":"Biology; Gene expression profiling; DNA microarray; Transcriptome; Microarray; Complementary DNA; Gene; Computational biology; Genetics; Gene expression; Microarray analysis techniques","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004971228,0.0002607514,0.000352566,0.0006319297,0.0002802756,0.0004250219,0.0002119193,0.0003687209,0.0008025075],"category_scores_gemma":[0.0005580224,0.0001268575,0.0004122627,0.000539911,0.0001843061,0.0001990455,0.0001583645,0.0005032118,0.0003607833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004201554,"about_ca_system_score_gemma":0.0003190938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006419004,"about_ca_topic_score_gemma":0.001580734,"domain_scores_codex":[0.9995223,0.00006977283,0.00003798482,0.000144708,0.0001806257,0.00004459341],"domain_scores_gemma":[0.9996743,0.0001320365,0.00005108841,0.00003441171,0.00009097771,0.00001717293],"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":[0.00006707638,0.00002151045,0.00185757,0.00006869142,0.00001462101,0.00002804171,0.00002300973,0.0005371643,0.9921136,0.0001283725,0.0001284341,0.005011859],"study_design_scores_gemma":[0.00002553203,0.0003636938,0.07831965,0.00002680819,0.00012302,0.0004528938,0.0001456679,0.0256335,0.8863743,0.0008719447,0.007622921,0.00004015744],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.871345,0.00237349,0.1095994,0.0004307372,0.000115297,0.0002734164,0.01218491,0.0007236734,0.002954079],"genre_scores_gemma":[0.8055872,0.002358138,0.1725958,0.0005878435,0.00006934554,0.000906604,0.01406064,0.0001194612,0.003714971],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008025075,"threshold_uncertainty_score":0.00304842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1525654730015768,"score_gpt":0.2228474791078214,"score_spread":0.07028200610624458,"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."}}