{"id":"W2151263602","doi":"10.1021/ac401185g","title":"Universal Drag Tag for Direct Quantitative Analysis of Multiple MicroRNAs","year":2013,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Michael's Hospital; York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chemistry; microRNA; Drag; Quantitative analysis (chemistry); Computational biology; Chromatography; Aerospace engineering; Biochemistry; Gene","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":[0.001111932,0.0008652173,0.0005998628,0.0008500974,0.0003756063,0.0005479089,0.0007364611,0.0009175923,0.001448173],"category_scores_gemma":[0.001034654,0.0005204736,0.000451182,0.0006211317,0.0007068352,0.0005696559,0.000951381,0.001275511,0.0007634222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007034487,"about_ca_system_score_gemma":0.0003912581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002475581,"about_ca_topic_score_gemma":0.0005367719,"domain_scores_codex":[0.9984701,0.0002714713,0.00006876291,0.0005012394,0.0005536028,0.0001348017],"domain_scores_gemma":[0.9995093,0.0001797967,0.0001025316,0.00006349263,0.00009124054,0.0000535014],"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":[0.00003636262,0.00001922364,0.0001201345,0.00006998479,0.000008582648,0.00004154362,0.00003607315,0.0001838442,0.9937099,0.0007139531,0.00009761964,0.00496274],"study_design_scores_gemma":[0.000005560494,0.00005773131,0.0002781585,0.000006043877,0.000008854802,0.00009252284,0.000008939192,0.003530236,0.9935166,0.0001457532,0.002337656,0.0000118869],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3385002,0.002385913,0.6509221,0.000276172,0.0002270193,0.0003199654,0.0005047246,0.001950079,0.004913733],"genre_scores_gemma":[0.4579974,0.001191367,0.5321317,0.0002794218,0.00003107213,0.0007042855,0.0008093522,0.0001399344,0.006715477],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001448173,"threshold_uncertainty_score":0.005880594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01204672822157408,"score_gpt":0.2649227609896743,"score_spread":0.2528760327681002,"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."}}