{"id":"W3042438073","doi":"10.2196/17964","title":"Visualization Environment for Federated Knowledge Graphs: Development of an Interactive Biomedical Query Language and Web Application Interface","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institutes of Health","keywords":"Computer science; Query language; Information retrieval; Web search query; Query expansion; Web query classification; Visualization; World Wide Web; Data mining; Search engine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009010349,0.001506202,0.0009651511,0.002346336,0.0007843169,0.004437526,0.003749196,0.002056739,0.0127994],"category_scores_gemma":[0.01393848,0.001162814,0.002193752,0.001388531,0.00108183,0.005447533,0.004559473,0.002947768,0.004001186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001793298,"about_ca_system_score_gemma":0.002328497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004555046,"about_ca_topic_score_gemma":0.003642159,"domain_scores_codex":[0.9963951,0.001006292,0.0004963058,0.0006377803,0.001283742,0.0001808614],"domain_scores_gemma":[0.9912129,0.004782933,0.0004339633,0.001117286,0.001945245,0.0005076028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002192354,0.001078209,0.007603373,0.002625931,0.0005193822,0.00353314,0.007571939,0.04526735,0.07817104,0.1598725,0.1929753,0.4985896],"study_design_scores_gemma":[0.000534515,0.0003419555,0.002217377,0.0006723831,0.0001698386,0.001798011,0.0006593234,0.5156524,0.077055,0.07576843,0.3247263,0.0004045265],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00281935,0.00009634483,0.9097335,0.000698371,0.00004428446,0.0005310242,0.001371897,0.08197801,0.002727259],"genre_scores_gemma":[0.03995055,0.0002881332,0.9397433,0.0009528297,0.0000437749,0.001221292,0.005404989,0.008317996,0.004077078],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0127994,"threshold_uncertainty_score":0.04765183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01368877451368831,"score_gpt":0.3235609465621653,"score_spread":0.309872172048477,"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."}}