{"id":"W2047275114","doi":"10.1145/2682914.2682917","title":"Querying a web of linked data","year":2014,"lang":"en","type":"article","venue":"ACM SIGWEB Newsletter","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; World Wide Web; Data science; Context (archaeology); Set (abstract data type); Linked data; Focus (optics); Space (punctuation); 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":[0.009038656,0.0008139585,0.001319679,0.009589994,0.003421356,0.01420968,0.002655234,0.003020662,0.00652991],"category_scores_gemma":[0.03734555,0.001040595,0.002118739,0.01390936,0.002816321,0.01879707,0.009826454,0.003145702,0.002514811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002332312,"about_ca_system_score_gemma":0.003431047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00436866,"about_ca_topic_score_gemma":0.004783671,"domain_scores_codex":[0.9825746,0.006387143,0.001837237,0.002095406,0.006631202,0.0004744607],"domain_scores_gemma":[0.9837911,0.00765125,0.001016763,0.004842786,0.002073643,0.0006243059],"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":[0.0002922044,0.0002883493,0.006829514,0.001316829,0.0006166351,0.002785001,0.003453592,0.02787194,0.005083588,0.7038271,0.05322308,0.1944122],"study_design_scores_gemma":[0.00004989237,0.00004316911,0.001029108,0.0004999621,0.0001283656,0.001329788,0.001660553,0.06407975,0.005695761,0.6528913,0.2724832,0.0001090134],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04057814,0.006516248,0.8673074,0.01388481,0.0007364656,0.0005151788,0.01384503,0.01052394,0.04609277],"genre_scores_gemma":[0.2968364,0.008198874,0.6406774,0.003905223,0.0006427268,0.0006395523,0.03052079,0.002463919,0.01611513],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01420968,"threshold_uncertainty_score":0.04780155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06086610974530453,"score_gpt":0.2833359603344722,"score_spread":0.2224698505891677,"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."}}