{"id":"W1964998447","doi":"10.4236/ijg.2015.61007","title":"An OWL-Based Mobile GeoBI Context Ontology Enabling Location-Based and Context-Based Reasoning and Supporting Contextual Business Analysis","year":2015,"lang":"en","type":"article","venue":"International Journal of Geosciences","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre de Géomatique du Québec; Université Laval","funders":"","keywords":"Computer science; Ontology; Context (archaeology); Geospatial analysis; Context model; Context awareness; Context analysis; Web Ontology Language; Data science; Taxonomy (biology); Knowledge management; World Wide Web; Semantic Web; Artificial intelligence; Geography","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":[0.0008874734,0.0003623703,0.0004080513,0.001194607,0.0009250882,0.00192445,0.001071913,0.0006872755,0.00169152],"category_scores_gemma":[0.001852824,0.0003782086,0.000996499,0.001367147,0.0006078798,0.002861835,0.00204424,0.001263426,0.0006962055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009469449,"about_ca_system_score_gemma":0.00303027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01671856,"about_ca_topic_score_gemma":0.02501617,"domain_scores_codex":[0.9991226,0.0001248766,0.0001259045,0.0000984631,0.0004169836,0.0001112195],"domain_scores_gemma":[0.9994854,0.00007731175,0.00006005687,0.0001224163,0.0001910654,0.00006369712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002600968,0.0004483086,0.004879979,0.001155463,0.0001800962,0.002068188,0.001839615,0.01894627,0.03513553,0.5622836,0.03749745,0.3353054],"study_design_scores_gemma":[0.00009326307,0.0001262283,0.005577425,0.0007311878,0.0002718624,0.002702526,0.001848562,0.1758233,0.01770576,0.1434766,0.6514962,0.0001471063],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0222299,0.000881349,0.9439652,0.001509179,0.0004379759,0.0005956764,0.00363975,0.003129061,0.02361183],"genre_scores_gemma":[0.1811599,0.001906626,0.7960034,0.0008787159,0.000140837,0.0005398315,0.006961515,0.0003331577,0.01207596],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01671856,"threshold_uncertainty_score":0.03324252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02194034940470553,"score_gpt":0.3048498517611198,"score_spread":0.2829095023564143,"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."}}