{"id":"W2190412510","doi":"10.1186/s12864-015-2257-y","title":"Single-molecule real-time transcript sequencing facilitates common wheat genome annotation and grain transcriptome research","year":2015,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":143,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Science and Technology of the People's Republic of China; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Biology; Genetics; Genome; Common wheat; Genome project; Contig; Gene Annotation; Gene; Computational biology; Reference genome; Genomics; Comparative genomics; Whole genome sequencing; Sequence assembly; Transcriptome; Chromosome; Gene expression","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.001498698,0.0006365044,0.0004954271,0.0006145487,0.0004485511,0.001181411,0.0005450802,0.0008265434,0.002677545],"category_scores_gemma":[0.001347822,0.0002908017,0.0007904616,0.0007728979,0.0003841086,0.001079465,0.0006790604,0.001088097,0.001764784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003672698,"about_ca_system_score_gemma":0.0005205838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004994824,"about_ca_topic_score_gemma":0.001505909,"domain_scores_codex":[0.9992602,0.0001161623,0.00006221706,0.0003320964,0.0001681848,0.00006105839],"domain_scores_gemma":[0.998934,0.000372573,0.0002051251,0.0001631202,0.0002545125,0.00007066983],"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":[0.0001499918,0.00004014051,0.00297208,0.0005357037,0.00003909185,0.0001090125,0.0001488758,0.001066937,0.958695,0.0006774693,0.0008388142,0.03472697],"study_design_scores_gemma":[0.0000621781,0.0004209638,0.03900121,0.0002072674,0.0002455175,0.0008487875,0.0003655975,0.05074879,0.8533573,0.004339284,0.05031262,0.00009058074],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4411702,0.00723843,0.5289351,0.001261662,0.0004723883,0.0003079561,0.01087344,0.00416065,0.005580182],"genre_scores_gemma":[0.5096328,0.004747507,0.4616955,0.0006687578,0.0002478516,0.000341632,0.01802831,0.0007308688,0.003906737],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002677545,"threshold_uncertainty_score":0.008957326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1143901562011854,"score_gpt":0.2828383985527866,"score_spread":0.1684482423516012,"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."}}