{"id":"W118265584","doi":"10.5220/0002147401730180","title":"MATCHING FOR MOBILE USERS IN THE PUBLISH/SUBSCRIBE PARADIGM","year":2007,"lang":"en","type":"article","venue":"","topic":"Smart Cities and Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Publication; Matching (statistics); Mobile computing; Computer network; World Wide Web; Business","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":[0.005932863,0.0004523889,0.001878609,0.000945419,0.003430344,0.006789305,0.002502546,0.005003854,0.0151011],"category_scores_gemma":[0.02142638,0.0009276275,0.001159152,0.002193119,0.002092444,0.01976612,0.004907275,0.002553352,0.00363608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001333552,"about_ca_system_score_gemma":0.002142283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0020811,"about_ca_topic_score_gemma":0.001484678,"domain_scores_codex":[0.9949896,0.001626396,0.0003705001,0.0008604422,0.001220688,0.0009323632],"domain_scores_gemma":[0.9874485,0.005997471,0.0006704135,0.003950677,0.001184397,0.0007485811],"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":[0.0011508,0.0003192663,0.002843342,0.0001315714,0.00005675003,0.0003986726,0.0008198929,0.01274671,0.00401113,0.883046,0.01019938,0.08427646],"study_design_scores_gemma":[0.0001278534,0.00008791975,0.0002733391,0.00001744831,0.00005433777,0.0004114331,0.0003791953,0.1421236,0.003208376,0.8423291,0.01094814,0.00003928566],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1282102,0.0004626848,0.8199577,0.00502415,0.0003289676,0.0003381348,0.0004699491,0.001523445,0.04368474],"genre_scores_gemma":[0.8268861,0.0003973646,0.1310557,0.0008704491,0.0004375054,0.0001961212,0.0004345247,0.0003792305,0.03934295],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0151011,"threshold_uncertainty_score":0.05051821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01504446961112219,"score_gpt":0.2284764959824276,"score_spread":0.2134320263713055,"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."}}