{"id":"W2026485377","doi":"10.1007/s007780200061","title":"Locating and accessing data repositories with WebSemantics","year":2002,"lang":"en","type":"article","venue":"The VLDB Journal","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Metadata; Computer science; World Wide Web; Data element; Interoperability; Data discovery; Data sharing; Metadata repository; Data mapping; Linked data; Semantics (computer science); Data publishing; Information retrieval; Data science; Semantic Web; Publishing; Database","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":[0.004102397,0.001076561,0.001535807,0.006725833,0.002709056,0.00693424,0.00284787,0.001610065,0.006106458],"category_scores_gemma":[0.01470374,0.00150833,0.001357951,0.01015719,0.001723497,0.01219069,0.008094511,0.001826221,0.003638674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007165212,"about_ca_system_score_gemma":0.00210597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004597711,"about_ca_topic_score_gemma":0.008527393,"domain_scores_codex":[0.9948502,0.0009491151,0.0007356157,0.0005393928,0.002587179,0.0003385038],"domain_scores_gemma":[0.9892827,0.003245854,0.0006665177,0.005232651,0.001126189,0.0004459831],"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":[0.001353139,0.0006564778,0.02404364,0.0008697966,0.0003143213,0.001647012,0.004372249,0.008461107,0.02896994,0.07657515,0.06245535,0.7902818],"study_design_scores_gemma":[0.0004765501,0.0005964045,0.01252316,0.0006425648,0.0006170788,0.005165188,0.005599478,0.3690808,0.1098156,0.2183112,0.2767549,0.0004170946],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08839287,0.001108865,0.8028378,0.00132935,0.0002311942,0.0006216089,0.001244034,0.08112134,0.02311292],"genre_scores_gemma":[0.3168527,0.001126999,0.6528541,0.0004948357,0.000180834,0.0005134293,0.008023914,0.005559042,0.01439417],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00693424,"threshold_uncertainty_score":0.02169579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05989600271466623,"score_gpt":0.2653695745818546,"score_spread":0.2054735718671883,"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."}}