{"id":"W4233511830","doi":"10.2174/1389202033490105","title":"Xenopus Informatics","year":2003,"lang":"en","type":"article","venue":"Current Genomics","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Xenopus; Computer science; Informatics; Annotation; Relational database; Object (grammar); Computational biology; Data mining; Gene; Information retrieval; Database; Data science; Bioinformatics; Biology; Artificial intelligence; Genetics; Engineering","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":[0.001234803,0.001060174,0.0006429974,0.002918693,0.0013117,0.003140733,0.001525655,0.0005001606,0.09998856],"category_scores_gemma":[0.002067176,0.0005629464,0.0006020106,0.003201339,0.0003675356,0.002098265,0.001506156,0.00100276,0.06210396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00102579,"about_ca_system_score_gemma":0.001431934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002479001,"about_ca_topic_score_gemma":0.00291478,"domain_scores_codex":[0.9994563,0.00008223741,0.00008363982,0.0001542927,0.0001662235,0.00005726179],"domain_scores_gemma":[0.9991704,0.000155283,0.0001020232,0.0002575163,0.0001877032,0.0001270516],"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":[0.00126773,0.0001557839,0.004563761,0.002336791,0.00007423387,0.0006012316,0.0008760098,0.0009701484,0.0344362,0.06533581,0.5691438,0.3202386],"study_design_scores_gemma":[0.00002776396,0.0000388554,0.001742042,0.0001605904,0.00002612716,0.0004585297,0.00009006931,0.0005979994,0.00809555,0.00329103,0.9854479,0.00002340097],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.01427915,0.007896373,0.1272369,0.001652957,0.0009687784,0.0007922304,0.2753936,0.1637278,0.4080521],"genre_scores_gemma":[0.04503039,0.007488731,0.1678929,0.0009239321,0.000336589,0.00108709,0.6326981,0.02100828,0.1235339],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.09998856,"threshold_uncertainty_score":0.3344951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02389652235166021,"score_gpt":0.291785315000355,"score_spread":0.2678887926486948,"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."}}