{"id":"W2626970493","doi":"10.1038/nplants.2017.99","title":"Genome sequencing: Illuminating the sunflower genome","year":2017,"lang":"en","type":"letter","venue":"Nature Plants","topic":"Sunflower and Safflower Cultivation","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Genome; Biology; Gene; Sunflower; Genetics; Genome size; Computational biology; Candidate gene; Evolutionary biology; Agronomy","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":[0.003878637,0.0006584633,0.0005304064,0.00043049,0.00116327,0.001321226,0.000835986,0.01154463,0.005401492],"category_scores_gemma":[0.009979942,0.0003617804,0.0006438101,0.0002620559,0.001158404,0.001416824,0.001048101,0.01212244,0.003324593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00188954,"about_ca_system_score_gemma":0.001463906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004029396,"about_ca_topic_score_gemma":0.00923385,"domain_scores_codex":[0.9987167,0.0002431089,0.00010444,0.0001696266,0.0006068991,0.0001591731],"domain_scores_gemma":[0.9959066,0.001744487,0.000224127,0.0002758132,0.0007266077,0.001122424],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001786963,0.00004118125,0.0006407037,0.00005820484,0.00002042837,0.0003885994,0.00003644346,0.0001221814,0.002966057,0.00185956,0.9404575,0.05323042],"study_design_scores_gemma":[0.0001717297,0.0001196189,0.002098128,0.00008680458,0.00003073476,0.0005579452,0.00005488282,0.0008099253,0.003368586,0.0103157,0.9823538,0.00003209519],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.003137882,0.01052448,0.006415178,0.870017,0.09726593,0.0001368656,0.0007652458,0.0005158203,0.01122159],"genre_scores_gemma":[0.01867997,0.01048145,0.008046334,0.778191,0.1311576,0.0003070982,0.001327082,0.0002123958,0.05159704],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01154463,"threshold_uncertainty_score":0.02051246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02737203740556188,"score_gpt":0.234665387644221,"score_spread":0.2072933502386592,"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."}}