{"id":"W2415670807","doi":"10.1007/978-1-4939-0835-6_9","title":"RNA Amplification for Pseudogene Detection Using RNA-Seq","year":2014,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Alberta Ministry of Agriculture and Forestry; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"RNA; Pseudogene; Biology; Complementary DNA; Non-coding RNA; Computational biology; DNA; Molecular biology; DNA microarray; Genetics; Gene; Gene expression; Genome","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":[0.002082776,0.002615661,0.001723445,0.001546817,0.001575754,0.001550157,0.00186729,0.001665018,0.005899307],"category_scores_gemma":[0.002973423,0.001813549,0.002773751,0.001229221,0.001373326,0.0008476925,0.001511071,0.005255186,0.007790895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000678185,"about_ca_system_score_gemma":0.00139695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009714488,"about_ca_topic_score_gemma":0.003724055,"domain_scores_codex":[0.996348,0.0006723497,0.0003111647,0.001125071,0.001106441,0.0004369622],"domain_scores_gemma":[0.9975958,0.0009264761,0.0001627984,0.000694534,0.00048514,0.0001352174],"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":[0.00008471456,0.0000344506,0.0001811034,0.0001756686,0.00002494495,0.00006612084,0.00007232751,0.0002864075,0.9919186,0.0007762625,0.000682999,0.005696489],"study_design_scores_gemma":[0.00001744535,0.00007006367,0.000616795,0.00001863904,0.00003689323,0.0001194797,0.00002071669,0.005359991,0.9818906,0.0005530431,0.01126773,0.00002878725],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04763794,0.0006432753,0.9273529,0.0003429483,0.0005375261,0.001819759,0.007600463,0.008435835,0.005629275],"genre_scores_gemma":[0.09097999,0.0008904221,0.8631788,0.001337979,0.0001347363,0.002798066,0.02459536,0.004122514,0.01196217],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005899307,"threshold_uncertainty_score":0.01973516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03488208414382578,"score_gpt":0.4174080180930585,"score_spread":0.3825259339492327,"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."}}