{"id":"W2561592872","doi":"10.1038/srep39373","title":"Deep sequencing of wheat sRNA transcriptome reveals distinct temporal expression pattern of miRNAs in response to heat, light and UV","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Plant Molecular Biology Research","field":"Agricultural and Biological Sciences","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; University of Manitoba","funders":"Agriculture and Agri-Food Canada","keywords":"Biology; Transcriptome; microRNA; Gene; Gene expression; Context (archaeology); Abiotic stress; Deep sequencing; Small RNA; Abiotic component; Genetics; Regulation of gene expression; Adaptation (eye); Computational biology; Genome; Ecology","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":[0.0001319865,0.0001722237,0.0002819787,0.0001709238,0.0002201082,0.0002855315,0.00008444056,0.000171323,0.0006215062],"category_scores_gemma":[0.0001269824,0.0001607373,0.0003185436,0.0002037426,0.0001193073,0.0001723979,0.0002216213,0.0003310554,0.0002374349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001494771,"about_ca_system_score_gemma":0.0001636748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007298121,"about_ca_topic_score_gemma":0.001995726,"domain_scores_codex":[0.9998934,0.000008074783,0.00000704709,0.00005326116,0.00001882661,0.00001939907],"domain_scores_gemma":[0.9999343,0.00001249484,0.00001641732,0.000008874581,0.00001609929,0.00001176528],"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":[0.0001112644,0.000009818169,0.002167594,0.00003231989,0.00001027748,0.00002414713,0.00008301262,0.00009973158,0.9936013,0.00005686579,0.00006941734,0.00373428],"study_design_scores_gemma":[0.00004441617,0.0005382082,0.5177873,0.00002778237,0.0001444376,0.0005347874,0.0004158147,0.008076639,0.4614155,0.0006506255,0.01032329,0.00004115302],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9899306,0.0005855978,0.006423884,0.00005113426,0.00001652722,0.00001510847,0.002054823,0.00006396996,0.0008583249],"genre_scores_gemma":[0.9835734,0.0003947146,0.008420629,0.0001105662,0.000009399218,0.00005341804,0.005313648,0.00003108685,0.002093142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007298121,"threshold_uncertainty_score":0.002079129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02233352630403047,"score_gpt":0.2529412763634992,"score_spread":0.2306077500594687,"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."}}