{"id":"W23877756","doi":"","title":"SEMANTIC HETEROGENEITY OF GEODATA","year":2002,"lang":"en","type":"article","venue":"","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Semantic heterogeneity; Computer science; Semantic grid; Semantic computing; Spatial heterogeneity; Information retrieval; Semantic similarity; Semantic Web","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":[0.02068301,0.0004238009,0.001021944,0.005826574,0.003229743,0.01241984,0.002409197,0.001801345,0.002248839],"category_scores_gemma":[0.05031519,0.0008153058,0.001219866,0.008698267,0.007930761,0.02546158,0.01185064,0.002949337,0.0004827034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003697175,"about_ca_system_score_gemma":0.00340979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003734145,"about_ca_topic_score_gemma":0.002143538,"domain_scores_codex":[0.9720218,0.01081565,0.00275538,0.002419493,0.01092191,0.00106584],"domain_scores_gemma":[0.9569678,0.0191991,0.003794778,0.01449998,0.004714938,0.0008234007],"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":[0.00003773632,0.00002039468,0.004734572,0.0001925387,0.00009191382,0.0003028117,0.002792307,0.004393144,0.0007330137,0.9459304,0.003400315,0.03737091],"study_design_scores_gemma":[0.000009043193,0.00001932424,0.001655396,0.0001804395,0.00006464546,0.000553873,0.002481736,0.009614502,0.001265346,0.921792,0.06232787,0.00003575957],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0884698,0.004736332,0.8424272,0.01944963,0.0003855031,0.0002155698,0.001346321,0.0009816698,0.04198798],"genre_scores_gemma":[0.8929185,0.002461272,0.09574001,0.002322067,0.0004175335,0.000257784,0.001710793,0.0003202308,0.003851803],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02068301,"threshold_uncertainty_score":0.1093835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0402596094850267,"score_gpt":0.236410829050712,"score_spread":0.1961512195656853,"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."}}