{"id":"W2083779647","doi":"10.1139/g06-124","title":"Erratum: LegumeDB bioinformatics resource: comparative genomic analysis and novel cross genera marker identification in lupin and pasture legume species","year":2006,"lang":"en","type":"erratum","venue":"Genome","topic":"Botanical Research and Chemistry","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biology; GenBank; Singlet state; Contig; Botany; Genetics; Genome; Physics; Gene","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0009896731,0.002439074,0.001938537,0.004569021,0.001771023,0.002267748,0.002125243,0.001986158,0.1547436],"category_scores_gemma":[0.008112839,0.000964982,0.001320063,0.006899472,0.0004002015,0.001585704,0.001263088,0.002437033,0.09843807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008922555,"about_ca_system_score_gemma":0.002304569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007746907,"about_ca_topic_score_gemma":0.01014111,"domain_scores_codex":[0.9989607,0.0001582337,0.0001906441,0.000210062,0.0003484514,0.0001319214],"domain_scores_gemma":[0.9965402,0.001057978,0.0004177577,0.0004365891,0.001236223,0.0003112286],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004059276,0.00004434409,0.0008274082,0.001031789,0.00003615074,0.000277827,0.00008778607,0.0001427227,0.005824679,0.0004140781,0.9661306,0.02477686],"study_design_scores_gemma":[0.0000933869,0.00007863268,0.00536646,0.0002860491,0.00007038552,0.0005898928,0.0001468954,0.0003516824,0.002359361,0.00053765,0.9900671,0.000052385],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.01064581,0.008883155,0.03263267,0.01042814,0.1075902,0.0002893998,0.7682623,0.03099793,0.03027046],"genre_scores_gemma":[0.01074911,0.003176136,0.03748311,0.003187026,0.004044099,0.0002181598,0.8857108,0.007605217,0.04782635],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1547436,"threshold_uncertainty_score":0.517669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02315303658795353,"score_gpt":0.254287646695901,"score_spread":0.2311346101079475,"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."}}