{"id":"W2170041483","doi":"10.1093/sysbio/sys025","title":"NeXML: Rich, Extensible, and Verifiable Representation of Comparative Data and Metadata","year":2012,"lang":"en","type":"article","venue":"Systematic Biology","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":111,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; University of British Columbia","funders":"FP7 People: Marie-Curie Actions; Natural Sciences and Engineering Research Council of Canada; National Evolutionary Synthesis Center; National Science Foundation","keywords":"Computer science; XML; Metadata; Python (programming language); Interoperability; Data exchange; Software; External Data Representation; File format; Software engineering; Data science; Programming language; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.020091,0.001436392,0.00137326,0.009626634,0.002280825,0.01146042,0.005635513,0.00340851,0.01002712],"category_scores_gemma":[0.05782624,0.001816245,0.001945251,0.008440753,0.004627414,0.01750342,0.01166081,0.0041091,0.006899655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002514687,"about_ca_system_score_gemma":0.005731239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004619836,"about_ca_topic_score_gemma":0.005010696,"domain_scores_codex":[0.9883441,0.004467875,0.002542102,0.001181081,0.003092831,0.0003719534],"domain_scores_gemma":[0.9598826,0.02101822,0.002793236,0.01206821,0.00328509,0.0009526056],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005237113,0.0001481427,0.003717296,0.002288708,0.0001354389,0.001696691,0.005937476,0.01619416,0.01040352,0.5584977,0.1130182,0.287439],"study_design_scores_gemma":[0.00008025082,0.0000585487,0.0008774608,0.001075785,0.00005739082,0.0006363062,0.000547244,0.02278201,0.01009607,0.2359814,0.7276298,0.000177794],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.00279553,0.0007610193,0.9300067,0.001815566,0.0003773056,0.0003847645,0.01332334,0.04190241,0.00863323],"genre_scores_gemma":[0.03040433,0.001673552,0.9086408,0.001194268,0.0002811973,0.001311664,0.04334892,0.007709298,0.005436006],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.979909,"threshold_uncertainty_score":0.1062527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08421342510478297,"score_gpt":0.3356246268713076,"score_spread":0.2514112017665247,"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."}}