{"id":"W2268506948","doi":"10.14778/2824032.2824128","title":"S+EPPs","year":2015,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Graph Theory and Algorithms","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"SPARQL; Computer science; Component (thermodynamics); Graph; Theoretical computer science; Information retrieval; RDF; Semantic 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":[],"consensus_categories":[],"category_scores_codex":[0.0009141919,0.001061941,0.0005365159,0.0006763586,0.000402387,0.001687463,0.001669058,0.000469603,0.01451364],"category_scores_gemma":[0.00381531,0.0005468951,0.0008056494,0.0008394475,0.00048382,0.003011367,0.002228425,0.001018684,0.005922048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005704024,"about_ca_system_score_gemma":0.001002201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00333428,"about_ca_topic_score_gemma":0.003393061,"domain_scores_codex":[0.9989613,0.000154567,0.00009776049,0.0003060231,0.0003927338,0.0000875641],"domain_scores_gemma":[0.9983456,0.0004046659,0.00009560827,0.0007441249,0.0003446117,0.0000653709],"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":[0.001413621,0.0002811062,0.005118246,0.00114045,0.0001900085,0.000667872,0.000746616,0.04412558,0.05513176,0.07219938,0.1848882,0.6340971],"study_design_scores_gemma":[0.0002304385,0.0003925109,0.001989959,0.00007918023,0.0001152266,0.0007429475,0.000250142,0.5277666,0.1277236,0.06760506,0.2729916,0.0001127251],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02029672,0.0002320319,0.7380465,0.0003733845,0.0001549929,0.0002247172,0.004664461,0.2238858,0.01212136],"genre_scores_gemma":[0.27544,0.0004970863,0.6570864,0.00102356,0.0001291611,0.0004583708,0.02494121,0.0215316,0.01889249],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01451364,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0193053903847535,"score_gpt":0.2090325920791987,"score_spread":0.1897272016944452,"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."}}