{"id":"W2075694192","doi":"10.1186/1471-2105-13-s1-s2","title":"SPARQL Assist language-neutral query composer","year":2012,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Paul's Hospital; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canarie; Microsoft Research","keywords":"SPARQL; Computer science; Named graph; Semantics (computer science); World Wide Web; Identifier; Information retrieval; Semantic Web; Query language; Context (archaeology); Task (project management); RDF query language; SPARK (programming language); RDF; Web search query; Web query classification; Programming language; Search engine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002304126,0.0001411205,0.0001377376,0.00003403047,0.00006911314,0.00002575673,0.0001844101,0.0002071322,0.00002196123],"category_scores_gemma":[0.00008799561,0.0001123963,0.00008836266,0.00006774796,0.0001389689,0.000008123635,0.00008490383,0.0001015194,0.0001518206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009258494,"about_ca_system_score_gemma":0.0000399878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009243166,"about_ca_topic_score_gemma":0.0000208791,"domain_scores_codex":[0.9991393,0.00002817967,0.0002486647,0.00008845462,0.000113965,0.0003814281],"domain_scores_gemma":[0.9994131,0.00002294187,0.00008572777,0.000298054,0.00002476388,0.000155358],"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":[0.0004344322,0.001217227,0.3463103,0.001330908,0.0004908699,0.00001032285,0.008086129,0.0001751903,0.04240037,0.003893892,0.3921103,0.2035401],"study_design_scores_gemma":[0.002395054,0.0006590981,0.09687769,0.00009864901,0.0001169125,0.0002361766,0.006620283,0.005738946,0.115586,0.00009902979,0.7700929,0.001479226],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8884607,0.003086323,0.08338615,0.0001994361,0.001158296,0.0002493224,0.00006073668,0.0001566343,0.02324242],"genre_scores_gemma":[0.8383229,0.00006809138,0.1581334,0.0009599303,0.0007223969,0.00001425316,0.0002669723,0.00002195205,0.001490045],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3779827,"threshold_uncertainty_score":0.4583389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02285940336895057,"score_gpt":0.2831718068025856,"score_spread":0.260312403433635,"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."}}