{"id":"W2483703040","doi":"10.4018/978-1-61520-655-1.ch044","title":"Spatial Subscriptions in Distributed Event-Based Systems","year":2012,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Peer-to-Peer Network Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Overlay; Event (particle physics); Spatial relation; Filter (signal processing); Relation (database); Distributed computing; Spatial analysis; Data mining; Theoretical computer science; Geography; Artificial intelligence; Programming language; Remote sensing; Computer vision","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":[0.00178898,0.0004613081,0.0005438552,0.0005819441,0.0008052813,0.004370796,0.001008588,0.001198592,0.00731255],"category_scores_gemma":[0.003666606,0.0005250428,0.0005141831,0.002179292,0.001435214,0.00585808,0.00197908,0.001764138,0.001912489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001387503,"about_ca_system_score_gemma":0.0008058728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001767144,"about_ca_topic_score_gemma":0.001509901,"domain_scores_codex":[0.9986334,0.000418099,0.0001251135,0.0002041187,0.0005358781,0.00008334986],"domain_scores_gemma":[0.9990795,0.0005666294,0.0000427317,0.0001743219,0.00009418873,0.00004256462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004322819,0.00003196021,0.000272776,0.000219453,0.00001307294,0.0002694768,0.000795079,0.01560913,0.001808461,0.9007837,0.006528161,0.07362543],"study_design_scores_gemma":[0.00004136145,0.00004445162,0.0003102322,0.0001345533,0.00003493143,0.0004462187,0.0005064001,0.08318204,0.003363836,0.5702685,0.34163,0.00003752584],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01249079,0.005219906,0.9122955,0.001464968,0.0004169952,0.0001542406,0.0003576607,0.00185451,0.06574549],"genre_scores_gemma":[0.4202832,0.01584169,0.4641968,0.0008073464,0.0006336662,0.0004155564,0.001303635,0.0005490426,0.09596901],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00731255,"threshold_uncertainty_score":0.02446288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02133833107525562,"score_gpt":0.2408081759362189,"score_spread":0.2194698448609633,"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."}}