{"id":"W2125153875","doi":"10.1104/pp.114.247668","title":"De Novo Genome Assembly of the Economically Important Weed Horseweed Using Integrated Data from Multiple Sequencing Platforms   ","year":2014,"lang":"en","type":"article","venue":"PLANT PHYSIOLOGY","topic":"Weed Control and Herbicide Applications","field":"Agricultural and Biological Sciences","cited_by":104,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Biology; Genome; Genetics; Sequence assembly; Whole genome sequencing; DNA sequencing; Reference genome; Genome size; Gene; Computational biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008932107,0.001047188,0.001542234,0.001853302,0.0009877383,0.001395211,0.0007374641,0.0007872037,0.001665435],"category_scores_gemma":[0.002049994,0.001062988,0.001957372,0.002503767,0.0002799285,0.0009116434,0.0009656923,0.001645101,0.00158749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008685088,"about_ca_system_score_gemma":0.001682806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008289489,"about_ca_topic_score_gemma":0.01676161,"domain_scores_codex":[0.9994465,0.00006321308,0.00005825873,0.0002409073,0.0001273142,0.00006374108],"domain_scores_gemma":[0.9989707,0.0002656883,0.0001635491,0.0001021389,0.0003821817,0.0001158172],"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":[0.001064659,0.0001788471,0.007271187,0.00141288,0.0003083465,0.001308838,0.001313616,0.01091332,0.9240088,0.001365158,0.003872109,0.04698212],"study_design_scores_gemma":[0.0005266378,0.001377094,0.1709283,0.0006145077,0.00199095,0.001762201,0.001480913,0.1706944,0.4698006,0.005182914,0.1750697,0.0005717153],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.586062,0.003067489,0.306321,0.0005173977,0.0003504926,0.001067011,0.09201755,0.005249519,0.005347619],"genre_scores_gemma":[0.2328144,0.002001639,0.5286241,0.0002191821,0.00007794948,0.000838109,0.2285569,0.002026866,0.004840824],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008289489,"threshold_uncertainty_score":0.01648247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04845462053304652,"score_gpt":0.2278643085522199,"score_spread":0.1794096880191734,"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."}}