{"id":"W2743184089","doi":"10.1139/cjm-2017-0230","title":"RNA extraction from decaying wood for (meta)transcriptomic analyses","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Microbiology","topic":"Forest Ecology and Biodiversity Studies","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agence Nationale de la Recherche; Deutsche Forschungsgemeinschaft","keywords":"RNA; RNA extraction; Transcriptome; Biology; Gene; Fungus; Polysaccharide; Extraction (chemistry); Botany; Gene expression; Biochemistry; Chemistry; Chromatography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001442161,0.0021675,0.001909054,0.00281515,0.001755264,0.001040428,0.001477747,0.001114048,0.004899707],"category_scores_gemma":[0.001239992,0.0008459477,0.001437139,0.002525734,0.0007234915,0.0006036999,0.000843604,0.002630598,0.006137819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003561131,"about_ca_system_score_gemma":0.001266841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009850299,"about_ca_topic_score_gemma":0.003010608,"domain_scores_codex":[0.9986206,0.0001835921,0.0001871821,0.0004483619,0.0003456824,0.0002145216],"domain_scores_gemma":[0.9990894,0.000271657,0.0001060647,0.0002023795,0.0002587348,0.0000717854],"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":[0.00008063253,0.00006176081,0.0003045136,0.0003530377,0.00001886354,0.0001925564,0.00006842025,0.0002093085,0.9924993,0.0001684264,0.0002404487,0.005802788],"study_design_scores_gemma":[0.0002014655,0.001707644,0.01630868,0.0003906676,0.0004362556,0.001033551,0.0004042471,0.004784463,0.8812681,0.002200332,0.09111952,0.0001449038],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2967752,0.01325262,0.5052319,0.0005337952,0.001491224,0.02124506,0.1331736,0.005923458,0.02237313],"genre_scores_gemma":[0.1523775,0.01179752,0.6412234,0.0008355032,0.0006869767,0.01745332,0.1606587,0.001374098,0.0135929],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004899707,"threshold_uncertainty_score":0.01639116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09728375236784502,"score_gpt":0.2768077506367588,"score_spread":0.1795239982689137,"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."}}