{"id":"W2085516557","doi":"10.1038/nsmb.1444","title":"Antisense transcripts are targets for activating small RNAs","year":2008,"lang":"en","type":"article","venue":"Nature Structural & Molecular Biology","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":272,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of General Medical Sciences; U.S. Public Health Service","keywords":"Biology; Argonaute; Antisense RNA; RNA; Long non-coding RNA; Promoter; Gene expression; Gene; Molecular biology; Non-coding RNA; Small nucleolar RNA; Cell biology; Genetics; RNA interference","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":[0.0004373388,0.0005835175,0.0003460026,0.0003781343,0.0004873142,0.001102771,0.000350388,0.0006875287,0.003420137],"category_scores_gemma":[0.0006605217,0.0004048047,0.0004590052,0.0001659617,0.0004967698,0.0004474295,0.0005769542,0.001214806,0.002641561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000326061,"about_ca_system_score_gemma":0.0001628767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001425909,"about_ca_topic_score_gemma":0.0002622066,"domain_scores_codex":[0.9996673,0.0000530826,0.00001714363,0.00009492119,0.0001184148,0.00004904331],"domain_scores_gemma":[0.9994918,0.0001965937,0.00007004572,0.0000632464,0.0000797693,0.00009854947],"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":[0.00006105752,0.00001005089,0.0002477983,0.00001676437,0.000003564591,0.0001261396,0.00002792102,0.00008653997,0.9947658,0.002646514,0.0001346719,0.001873122],"study_design_scores_gemma":[0.00001331106,0.0001163698,0.001155342,0.000004303772,0.00001920614,0.0004968353,0.00005543389,0.001068296,0.9871574,0.002185598,0.007719999,0.000007927512],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8789688,0.002891749,0.08994954,0.0007938867,0.0008574458,0.00007954797,0.0005018442,0.001445333,0.02451177],"genre_scores_gemma":[0.9737347,0.0007869484,0.009405001,0.0003391218,0.000163606,0.00004416046,0.0006678204,0.0002658076,0.0145929],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003420137,"threshold_uncertainty_score":0.01144153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01306207801450982,"score_gpt":0.3067119378618558,"score_spread":0.293649859847346,"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."}}