{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002551086,0.0001079653,0.0002476453,0.00007926704,0.00008565774,0.00002854725,0.0001716001,0.00008613116,0.00007165804],"category_scores_gemma":[0.0003276048,0.00003688812,0.00005820683,0.0004024687,0.0001647352,0.00008784216,0.00009974928,0.00006024227,0.0000028471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003487628,"about_ca_system_score_gemma":0.00002844666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002249169,"about_ca_topic_score_gemma":0.0007167345,"domain_scores_codex":[0.9979953,0.0003000262,0.0004975717,0.0005455412,0.0003609628,0.0003006611],"domain_scores_gemma":[0.9992998,0.0001683799,0.0001196335,0.0001753842,0.00009565149,0.0001411795],"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":[0.0001115264,0.00002301748,0.181862,0.00001012886,0.000002074456,0.0001409907,0.0001598859,3.053336e-7,0.8137574,2.987535e-7,0.000181766,0.003750663],"study_design_scores_gemma":[0.0001081895,0.0001903611,0.2914068,0.0003262957,0.000002692189,0.0001287789,0.00009449379,0.000004968428,0.7062418,0.0002607561,0.001117524,0.0001173237],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982087,0.0001318628,0.00002935049,0.0009996801,0.000266935,0.0002751525,0.00001820353,0.00001133179,0.0000587882],"genre_scores_gemma":[0.9994659,0.000003758246,0.00007140905,0.00001437222,0.00001478485,0.00001112347,0.00001295419,0.000001016113,0.0004046434],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1095448,"threshold_uncertainty_score":0.1504254,"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."}}