{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003558088,0.000163875,0.0001341445,0.00006417346,0.0000953504,0.00005398878,0.0002899498,0.0001338399,0.00004430454],"category_scores_gemma":[0.0002688321,0.0001482979,0.00009238397,0.00009341497,0.0001422728,0.000004341463,0.000130432,0.0001586981,0.0002271458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003309387,"about_ca_system_score_gemma":0.0002432195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.523217e-7,"about_ca_topic_score_gemma":0.000003238842,"domain_scores_codex":[0.9987617,0.00003437567,0.0003985126,0.000146554,0.0002354633,0.0004234248],"domain_scores_gemma":[0.9991385,0.00001044202,0.00009353333,0.0004059158,0.0001103689,0.0002412308],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000196012,0.001019927,0.009694046,0.001103322,0.0003451296,0.00000537984,0.002580467,0.000386873,0.2470843,0.006805865,0.1669921,0.5637865],"study_design_scores_gemma":[0.0004604898,0.0001510101,0.000152862,0.000008451489,0.000009712485,0.00001146956,0.0002322941,0.0002714633,0.05574603,0.000280364,0.9424538,0.0002220308],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9514263,0.003845663,0.01997415,0.00009414343,0.002067708,0.000506339,0.00006742261,0.00003227396,0.02198606],"genre_scores_gemma":[0.975915,0.00943233,0.01122357,0.0005129386,0.0006744289,0.0000323887,0.000515287,0.00005291514,0.001641167],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7754617,"threshold_uncertainty_score":0.6047413,"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."}}