{"id":"W2805208499","doi":"","title":"SPARQL Assist Language-Neutral Query Composer.","year":2010,"lang":"en","type":"article","venue":"","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Paul's Hospital; University of British Columbia","funders":"","keywords":"SPARQL; Computer science; Identifier; Task (project management); Query language; Named graph; Information retrieval; Composition (language); World Wide Web; Natural language processing; Linguistics; Semantic Web; Programming language; RDF","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":[0.008449201,0.001504054,0.0009578399,0.001030232,0.0009049864,0.003581516,0.003280374,0.001408579,0.05036239],"category_scores_gemma":[0.01692108,0.000913367,0.001242856,0.001139774,0.0009962883,0.005275876,0.004596163,0.001983741,0.02723007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001048319,"about_ca_system_score_gemma":0.001545287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002303718,"about_ca_topic_score_gemma":0.001980005,"domain_scores_codex":[0.9938123,0.001540265,0.0007957544,0.001233166,0.002096157,0.0005223644],"domain_scores_gemma":[0.9914659,0.003288484,0.0003223947,0.002567127,0.001965428,0.0003905914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002614561,0.0004656865,0.005066082,0.00215305,0.0002549835,0.001668559,0.002431521,0.004957174,0.05024034,0.08815943,0.4057258,0.4362628],"study_design_scores_gemma":[0.0003321419,0.0001860454,0.001531613,0.0003415868,0.0001302781,0.002027732,0.0007246172,0.08560536,0.0940646,0.07413241,0.7407284,0.0001952445],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.006764037,0.0004865614,0.6831341,0.001272872,0.0003246358,0.0009424925,0.008805375,0.2777354,0.02053452],"genre_scores_gemma":[0.178822,0.0009479893,0.6692709,0.004314619,0.0004620581,0.001241223,0.04449479,0.05301266,0.04743365],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.05036239,"threshold_uncertainty_score":0.168479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005958568575716292,"score_gpt":0.270039079173995,"score_spread":0.2640805105982787,"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."}}