{"id":"W1014077357","doi":"10.1016/j.dib.2015.06.016","title":"Construction of Brassica A and C genome-based ordered pan-transcriptomes for use in rapeseed genomic research","year":2015,"lang":"en","type":"article","venue":"Data in Brief","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"National Key Research and Development Program of China; National High-tech Research and Development Program; Biotechnology and Biological Sciences Research Council; Directorate for Biological Sciences; National Natural Science Foundation of China","keywords":"Genome; Brassica rapa; Brassica; Brassica oleracea; Biology; Whole genome sequencing; Rapeseed; Computational biology; Genetics; Reference genome; Gene; Transcriptome; Genome project; DNA sequencing; Genomics; Botany; Gene expression","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0006270963,0.00008472749,0.0001612166,0.0001039721,0.00002748158,0.00002081217,0.0002287305,0.00007992729,0.000001039519],"category_scores_gemma":[0.0002243435,0.00008730897,0.00001632112,0.0001168593,0.0002061104,0.000002767081,0.0001802764,0.0000615742,2.931589e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001410421,"about_ca_system_score_gemma":0.000152341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000401577,"about_ca_topic_score_gemma":0.00113476,"domain_scores_codex":[0.9990796,0.0000772536,0.0002112745,0.0003461853,0.0000841975,0.0002014858],"domain_scores_gemma":[0.9992985,0.0000554185,0.00004154,0.000455932,0.0001043743,0.0000441958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004151447,0.00006946092,0.07551473,0.00004392199,0.00003045812,0.000001209177,0.0001118343,0.00003642679,0.9213532,0.0000889491,0.0003794208,0.00195523],"study_design_scores_gemma":[0.01174065,0.001153702,0.7139668,0.00005360802,0.00003848498,0.00001402072,0.001201628,0.001729537,0.07433143,0.00108646,0.1940917,0.0005919448],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966619,0.001640759,0.0003375616,0.0001288727,0.00005136141,0.0003580842,0.00078318,0.000001093422,0.00003718408],"genre_scores_gemma":[0.9919301,0.0002602511,0.00701393,0.00004689874,0.00004045046,0.00003026574,0.0006513823,0.0000122495,0.00001453364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8470218,"threshold_uncertainty_score":0.3560356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1341821578572356,"score_gpt":0.3427820904941575,"score_spread":0.2085999326369219,"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."}}