{"id":"W2804457431","doi":"10.1007/978-1-4939-7737-6_10","title":"Navigating Xenbase: An Integrated Xenopus Genomics and Gene Expression Database","year":2018,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Physiological and biochemical adaptations","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","keywords":"Ensembl; Xenopus; UniProt; Biology; Computational biology; Genome; Gene; Model organism; Gene nomenclature; Genomics; Database; Genetics; Computer science","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":[0.0004285446,0.0001086923,0.0001325125,0.000009868745,0.00007018391,0.000007799967,0.0001721366,0.0001084231,0.0002167615],"category_scores_gemma":[0.0002216857,0.00007828056,0.00001849806,0.0001645257,0.0004634398,0.00004405627,0.0003180978,0.0001937134,0.00001592139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003458732,"about_ca_system_score_gemma":0.000004573324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001800209,"about_ca_topic_score_gemma":0.00001569845,"domain_scores_codex":[0.9986641,0.0005304052,0.0001679992,0.0003915485,0.00003874023,0.0002071918],"domain_scores_gemma":[0.9995792,0.00007814868,0.00004582477,0.0002024173,0.00000758867,0.00008685142],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001446198,0.00004030043,0.0007868462,0.000001028483,0.000001520998,0.000004049352,0.0000519397,0.00001316036,0.9563351,0.00005745291,0.000005610239,0.04268852],"study_design_scores_gemma":[0.0001285826,0.0001531577,0.0006814455,0.000007932291,0.000003067323,0.000005184278,0.00003199624,0.002071136,0.9885494,0.007228397,0.001019684,0.0001200384],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.62645,0.00004500438,0.3732658,0.00004088597,0.00003058617,0.0000608861,0.00001172303,0.00001392946,0.00008119186],"genre_scores_gemma":[0.2265618,0.00001194581,0.7729037,0.0004031781,0.00002187558,0.00001106028,0.00007566287,0.000005288068,0.000005475214],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3998882,"threshold_uncertainty_score":0.3192188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03394355044255309,"score_gpt":0.3812401770192344,"score_spread":0.3472966265766813,"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."}}