{"id":"W2162111699","doi":"10.1038/nmeth.1244","title":"Efficient microRNA capture and bar-coding via enzymatic oligonucleotide adenylation","year":2008,"lang":"en","type":"article","venue":"Nature Methods","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":53,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Human Genome Research Institute; Canadian Institutes of Health Research; National Institutes of Health","keywords":"Oligonucleotide; Multiplex; microRNA; Computational biology; Biology; Computer science; Bioinformatics; Biochemistry; 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":[0.00135752,0.0007952849,0.0006481709,0.0004095671,0.0004789935,0.0009490258,0.0007794722,0.001091272,0.002441765],"category_scores_gemma":[0.001227182,0.0009278888,0.000838066,0.0002884057,0.0006962473,0.0006853258,0.001226366,0.00216676,0.002872326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004938363,"about_ca_system_score_gemma":0.0004527805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001787634,"about_ca_topic_score_gemma":0.0005503023,"domain_scores_codex":[0.9986589,0.0002627314,0.00009105734,0.0004175337,0.0003525236,0.0002172701],"domain_scores_gemma":[0.9994419,0.0002423749,0.00009514546,0.0001132691,0.00005395364,0.00005331251],"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":[0.00006595364,0.00003209723,0.00007956871,0.00006147192,0.000008184921,0.00005452045,0.00003658536,0.000123056,0.9919397,0.002043325,0.0003407541,0.005214747],"study_design_scores_gemma":[0.00001167798,0.00007070159,0.0001636296,0.000004811969,0.000007045258,0.0001348354,0.000008621336,0.00119477,0.9937556,0.0002791708,0.004356676,0.00001245298],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2567468,0.002696391,0.7196525,0.001032382,0.0006493484,0.0009411295,0.001135075,0.003919472,0.01322687],"genre_scores_gemma":[0.6587166,0.001518951,0.3179519,0.000762752,0.0001382643,0.00109031,0.002717092,0.0005514782,0.01655266],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002441765,"threshold_uncertainty_score":0.008168519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01025782602503853,"score_gpt":0.3018404272804335,"score_spread":0.291582601255395,"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."}}