{"id":"W3009129594","doi":"10.5430/ijhe.v8n8p24","title":"Educating the Information Integration Using Contextual Knowledge and Ontology Merging in Advanced Levels","year":2019,"lang":"en","type":"article","venue":"International Journal of Higher Education","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Ontology; Information integration; XML; Data integration; RDF; Semantic integration; Ontology-based data integration; Information retrieval; Interface (matter); Architecture; World Wide Web; Software engineering; Data science; Semantic Web; Database; Semantic Web Stack; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003614117,0.00007692008,0.0001202274,0.0002807228,0.00003492206,0.0001426903,0.0004878786,0.00003893082,0.00003952658],"category_scores_gemma":[0.0001052409,0.00005545711,0.00003191138,0.0001364044,0.00002550269,0.001923659,0.00006732161,0.0001548666,0.00001596444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001620227,"about_ca_system_score_gemma":0.0003464685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000067488,"about_ca_topic_score_gemma":0.00002282312,"domain_scores_codex":[0.9991446,0.00007463643,0.0004104115,0.00008523288,0.0001908497,0.00009427423],"domain_scores_gemma":[0.9988,0.000186502,0.000403547,0.0001096183,0.0004759728,0.00002432142],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00006059448,0.000154696,0.02907815,0.00001704228,0.00005995841,0.000001810343,0.01781978,0.0006064192,0.004085521,0.1638563,0.000449792,0.78381],"study_design_scores_gemma":[0.001786397,0.0002376224,0.9220511,0.000624366,0.00002250256,0.0006754254,0.008124884,0.0211302,0.002191291,0.01630303,0.02650558,0.0003476387],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9737996,0.001053613,0.01221997,0.004263838,0.005963766,0.0001142004,4.288352e-7,0.000009775149,0.0025748],"genre_scores_gemma":[0.9929087,0.0000145037,0.006294584,0.0003592305,0.0001682288,0.000002874906,0.000001372238,0.000002554416,0.0002479253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8929729,"threshold_uncertainty_score":0.2261475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02361144798350379,"score_gpt":0.3442375831366786,"score_spread":0.3206261351531748,"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."}}