{"id":"W2107047397","doi":"10.14778/1687553.1687600","title":"SMDM","year":2009,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; Ontology; Semantics (computer science); RDF; Business domain; IBM; Domain (mathematical analysis); Software engineering; Semantic Web; Business rule; Business process; Information retrieval; Programming language; Engineering","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":[0.002388339,0.0005019718,0.0004676413,0.001524021,0.001137551,0.004383196,0.002236654,0.001317408,0.0346682],"category_scores_gemma":[0.004133022,0.0003221667,0.0008644941,0.002997346,0.0006304209,0.005310522,0.004464703,0.00137582,0.01896568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001406909,"about_ca_system_score_gemma":0.002448165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002803029,"about_ca_topic_score_gemma":0.003354604,"domain_scores_codex":[0.9975019,0.0005469349,0.000246588,0.0005018988,0.000935662,0.0002668923],"domain_scores_gemma":[0.9974098,0.0003083859,0.0001142616,0.001154878,0.0008515713,0.0001611186],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001791638,0.0001406275,0.001773178,0.0004763678,0.00004917406,0.0004583096,0.0004214386,0.004470195,0.006642279,0.4128101,0.1909099,0.3816693],"study_design_scores_gemma":[0.00002330713,0.00002984714,0.000352474,0.00006583104,0.00001320542,0.0003353199,0.000137184,0.01590261,0.0040965,0.04437037,0.934658,0.00001542168],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01053394,0.001430209,0.6894814,0.005365724,0.001401356,0.0005980491,0.007281846,0.01759004,0.2663174],"genre_scores_gemma":[0.181897,0.003102394,0.5896413,0.003829068,0.0009148349,0.0009287786,0.04036116,0.003614149,0.1757114],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.0346682,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009923090580914845,"score_gpt":0.21368471931581,"score_spread":0.2037616287348951,"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."}}