{"id":"W3021407037","doi":"10.1002/aps3.11345","title":"A two‐tier bioinformatic pipeline to develop probes for target capture of nuclear loci with applications in Melastomataceae","year":2020,"lang":"en","type":"article","venue":"Applications in Plant Sciences","topic":"Chromosomal and Genetic Variations","field":"Agricultural and Biological Sciences","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Indian Institute of Science Education and Research Mohali; University of Colombo; Natural Sciences and Engineering Research Council of Canada; Universidade Estadual Paulista; Indian Institute of Science Education and Research Thiruvananthapuram; Society for the Study of Evolution; Botanical Society of America; National University of Singapore; Indian Institute of Science; University of Florida; Society of Systematic Biologists; Florida Museum of Natural History; American Society of Plant Taxonomists; Inyuvesi Yakwazulu-Natali; National Science Foundation","keywords":"Melastomataceae; Biology; Pipeline (software); Modularity (biology); Computational biology; Evolutionary biology; Botany; Computer science; Operating system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001710004,0.0001057747,0.00016221,0.00004268364,0.0001880054,0.00003297373,0.000415191,0.00003816732,0.00003357054],"category_scores_gemma":[0.00004056413,0.00004412432,0.00002083323,0.002529337,0.0001054082,0.0001011988,0.00005867757,0.00005476255,0.00001367908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001482054,"about_ca_system_score_gemma":0.00004629382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001505927,"about_ca_topic_score_gemma":0.001463798,"domain_scores_codex":[0.9990404,0.00001383967,0.0003143423,0.0002697061,0.0001645262,0.0001971477],"domain_scores_gemma":[0.9995083,0.0001694586,0.0001016029,0.00005614298,0.00007996433,0.00008451408],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002641895,0.0023794,0.357813,0.0005294833,0.00007097871,0.000002516067,0.04944797,0.02367429,0.1449221,0.379165,0.0110449,0.0306862],"study_design_scores_gemma":[0.001571606,0.001228908,0.2092359,0.0001785092,0.00004934919,0.00002131985,0.033979,0.03788472,0.01101989,0.01114744,0.6921816,0.001501754],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9648535,0.0001565527,0.01274924,0.01521778,0.00002105762,0.004310873,0.001142031,0.00008810362,0.001460889],"genre_scores_gemma":[0.9590568,0.000007255619,0.03942145,0.0004841591,0.00004732974,0.0007466776,0.0002208504,0.000001118337,0.00001436112],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6811367,"threshold_uncertainty_score":0.1799338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01956495004714514,"score_gpt":0.226430569047449,"score_spread":0.2068656190003039,"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."}}