{"id":"W2113390076","doi":"10.1038/nmeth1130","title":"Using expression profiling data to identify human microRNA targets","year":2007,"lang":"en","type":"article","venue":"Nature Methods","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":399,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network; University of New Brunswick; Ontario Institute for Cancer Research; University of Toronto","funders":"National Cancer Institute","keywords":"microRNA; Computational biology; Biology; Gene expression profiling; Gene expression; Bioinformatics; Gene; Genetics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0009819794,0.0004812763,0.0006605205,0.001008861,0.0003208998,0.001064354,0.0002735362,0.0005325079,0.0009799924],"category_scores_gemma":[0.001515322,0.0003604582,0.0004459879,0.001095806,0.0002558205,0.000374949,0.0004013391,0.0009967254,0.001054668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003808518,"about_ca_system_score_gemma":0.0003051999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003009639,"about_ca_topic_score_gemma":0.0007586368,"domain_scores_codex":[0.9991238,0.0002057119,0.00006288353,0.0002444409,0.0002706986,0.00009243115],"domain_scores_gemma":[0.9993049,0.0003905098,0.0001008482,0.00008738379,0.00008462003,0.00003169875],"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":[0.0002983432,0.00006542153,0.006012309,0.000119772,0.00007443387,0.00009703092,0.00006104724,0.0006815922,0.9684568,0.0008073724,0.000446556,0.02287932],"study_design_scores_gemma":[0.00005026317,0.0003114651,0.03634579,0.00002847561,0.0002426019,0.0008066549,0.00007102596,0.02233531,0.9229698,0.002282498,0.01452221,0.00003401755],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.765171,0.00487829,0.2076532,0.0006155128,0.0001730235,0.0002273262,0.01104079,0.001255938,0.00898493],"genre_scores_gemma":[0.8743716,0.002749501,0.1020382,0.0006325843,0.0000909238,0.0005134278,0.01597111,0.0002579071,0.003374801],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.001064354,"threshold_uncertainty_score":0.005193293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08152713650975808,"score_gpt":0.4902602839792751,"score_spread":0.408733147469517,"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."}}