{"id":"W2098357503","doi":"10.1371/journal.pone.0050226","title":"Evaluating Methods for Isolating Total RNA and Predicting the Success of Sequencing Phylogenetically Diverse Plant Transcriptomes","year":2012,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":229,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Alberta; University of Toronto","funders":"National Institute on Drug Abuse; National Institute of Food and Agriculture; National Institutes of Health; University of Toronto; Max-Planck-Gesellschaft; University of Alberta; Western Canada Research Grid; Ministry of Advanced Education; National Science Foundation; Compute Canada; Universität zu Köln; Government of Alberta; Ministry of Advanced Education and Technology; Bill and Melinda Gates Foundation; Agency for Science, Technology and Research; Natural Sciences and Engineering Research Council of Canada; U.S. Department of Agriculture","keywords":"RNA; Biology; Transcriptome; Illumina dye sequencing; Deep sequencing; Computational biology; DNA sequencing; Genetics; Phylogenetic tree; RNA-Seq; Gene; Genome; Gene expression","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":[0.02193631,0.001856367,0.001348245,0.003796651,0.0008502206,0.002720469,0.001501008,0.001563509,0.0005282079],"category_scores_gemma":[0.03379418,0.0008499504,0.001535265,0.002869459,0.001403641,0.00230237,0.001382105,0.001694123,0.0006383589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001454737,"about_ca_system_score_gemma":0.001208792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00165045,"about_ca_topic_score_gemma":0.003937337,"domain_scores_codex":[0.9873387,0.003816143,0.001133058,0.002482236,0.00479698,0.0004328892],"domain_scores_gemma":[0.9563286,0.03093923,0.005325714,0.00193684,0.004660981,0.0008086771],"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":[0.001175046,0.0004824859,0.2299476,0.002824758,0.001779956,0.0002856514,0.0008463181,0.06164675,0.5330642,0.001232762,0.001210538,0.1655039],"study_design_scores_gemma":[0.0001113585,0.003463534,0.1750576,0.0003977103,0.001374291,0.0008679242,0.0008154814,0.4149263,0.388782,0.003663217,0.01014757,0.0003928583],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6512209,0.00996393,0.3317775,0.0004526153,0.0001452866,0.0006772057,0.002710646,0.001474378,0.001577523],"genre_scores_gemma":[0.4378036,0.004114013,0.5482734,0.0002205857,0.0001441479,0.001113968,0.006863489,0.0005886671,0.0008781755],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02193631,"threshold_uncertainty_score":0.1160117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1151025113604452,"score_gpt":0.3440252462852719,"score_spread":0.2289227349248267,"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."}}