{"id":"W2735305329","doi":"10.1002/cpe.4207","title":"Targeted content dissemination in mobile social networks taking account of resource limitation","year":2017,"lang":"en","type":"article","venue":"Concurrency and Computation Practice and Experience","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Computer science; Exploit; Relay; Computer network; Mobile social network; Scheduling (production processes); Overhead (engineering); Limiting; Mobile computing; Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003932135,0.0001074501,0.0001659701,0.00005663675,0.0004453815,0.0003027016,0.0002265072,0.00007116701,0.000002292347],"category_scores_gemma":[0.0001445093,0.000107999,0.00001974808,0.0001030018,0.0001688436,0.001772893,0.0001362127,0.0001357557,5.547973e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001358515,"about_ca_system_score_gemma":0.00003196942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000311007,"about_ca_topic_score_gemma":0.000002923448,"domain_scores_codex":[0.9989607,0.00009092211,0.0003191325,0.0002919621,0.000181992,0.0001553077],"domain_scores_gemma":[0.9985116,0.0004448624,0.0006714543,0.0001537209,0.0001668714,0.00005156557],"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":[0.00004013998,0.0000821987,0.002569374,0.00002124729,0.000007659195,0.00001297772,0.0239402,0.0003168523,0.0001282321,0.01008412,0.0001348841,0.9626621],"study_design_scores_gemma":[0.0004906793,0.0001128501,0.02576069,0.0001017486,0.00001175834,0.0000195627,0.006664349,0.9649005,0.00005008726,0.000413822,0.001281768,0.0001922085],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2834432,0.001204249,0.7135451,0.0004176045,0.0002127208,0.0001835932,0.000001436408,0.00002324194,0.0009688063],"genre_scores_gemma":[0.9976757,0.0003097635,0.001780481,0.0001217181,0.00004720663,0.00003419962,0.00001114304,0.000003684597,0.00001616773],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9645836,"threshold_uncertainty_score":0.4404072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05854052715219711,"score_gpt":0.3522446911425863,"score_spread":0.2937041639903892,"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."}}