{"id":"W4319655725","doi":"10.1093/genetics/iyad018","title":"Xenbase: key features and resources of the <i>Xenopus</i> model organism knowledgebase","year":2023,"lang":"en","type":"article","venue":"Genetics","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":112,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development","keywords":"Xenopus; Ensembl; Biology; UniProt; Computational biology; Model organism; Genome; Gene; Bioinformatics; Genetics; Genomics","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":[0.003315373,0.002879198,0.002664965,0.008259445,0.001714047,0.007759894,0.007382069,0.002967863,0.06969772],"category_scores_gemma":[0.01305464,0.002266507,0.001686631,0.0116749,0.000903827,0.007744195,0.00644187,0.003733566,0.1089663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002458879,"about_ca_system_score_gemma":0.005127233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00959873,"about_ca_topic_score_gemma":0.009434775,"domain_scores_codex":[0.9979645,0.0003262365,0.0004987352,0.0003623831,0.0006493516,0.0001988715],"domain_scores_gemma":[0.9947561,0.001170174,0.0006303609,0.001417124,0.001223344,0.0008028813],"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":[0.0003767071,0.00007716443,0.0007621443,0.003511946,0.0001142126,0.000467986,0.0002816507,0.001880831,0.00567938,0.008904058,0.919444,0.05849993],"study_design_scores_gemma":[0.00006811848,0.00002301308,0.0007268872,0.0006429324,0.00006162214,0.000332702,0.00006930182,0.001087785,0.003393817,0.004872442,0.9886346,0.00008665634],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.001701672,0.005784298,0.0860853,0.00235394,0.0009133498,0.0008467204,0.7193165,0.1442675,0.03873076],"genre_scores_gemma":[0.002885543,0.003249846,0.05393524,0.0008556122,0.0001353843,0.000718353,0.914604,0.01775241,0.005863493],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.06969772,"threshold_uncertainty_score":0.2331621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01057677359175394,"score_gpt":0.2163104187672056,"score_spread":0.2057336451754516,"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."}}