{"id":"W2135556068","doi":"10.1371/journal.pone.0086039","title":"Comprehensive Transcriptome Assembly of Chickpea (Cicer arietinum L.) Using Sanger and Next Generation Sequencing Platforms: Development and Applications","year":2014,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Genetic and Environmental Crop Studies","field":"Agricultural and Biological Sciences","cited_by":97,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; Saskatchewan Research Council (Canada); National Research Council Canada","funders":"Agricultural Research Service; Indo-German Science and Technology Centre; Ministry of Agriculture - Saskatchewan; Consortium of International Agricultural Research Centers; Department of Science and Technology, Ministry of Science and Technology, India; U.S. Department of Agriculture","keywords":"Contig; Transcriptome; Biology; Sanger sequencing; De novo transcriptome assembly; Genetics; Sequence assembly; Genome; Reference genome; Gene; Computational biology; Whole genome sequencing; DNA sequencing; Gene expression","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":[0.00004557648,0.0000727621,0.0001194376,0.000005582697,0.000175882,0.0000180789,0.00003116198,0.00003353913,0.0000126481],"category_scores_gemma":[0.000002559467,0.00003335209,0.00001057264,0.00004359217,0.00006359656,0.00004207193,0.00003222157,0.00003318952,0.00000180652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001458101,"about_ca_system_score_gemma":0.000001648892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004724243,"about_ca_topic_score_gemma":0.00005802201,"domain_scores_codex":[0.9995291,0.00000840138,0.0001210678,0.0001391601,0.0001079676,0.00009433826],"domain_scores_gemma":[0.9998574,0.00002533549,0.00004239898,0.0000224565,0.0000165339,0.00003592514],"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":[0.000002382835,0.00004597662,0.003993216,0.00002415991,0.00002508501,4.091168e-8,0.0004371024,0.000004666013,0.9814242,0.00002131598,0.000001057444,0.01402087],"study_design_scores_gemma":[0.000295073,0.0002203275,0.5858167,0.00008320914,0.0001223697,0.000004146714,0.002689936,0.002707562,0.4052121,0.0001498949,0.002336414,0.0003622312],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998991,0.0005161492,0.0001354816,0.00007172825,0.000005057444,0.0001571205,0.000003775778,0.000008593002,0.0001110828],"genre_scores_gemma":[0.9956855,0.0001123419,0.003984912,0.00009488319,0.00006644164,0.00001739103,0.00001410965,7.787814e-7,0.00002359875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5818235,"threshold_uncertainty_score":0.1360059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1580579365379646,"score_gpt":0.2160245914966311,"score_spread":0.05796665495866657,"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."}}