{"id":"W3037350926","doi":"10.65109/biov1668","title":"Influence Maximization in Unknown Social Networks: Learning Policies for Effective Graph Sampling","year":2020,"lang":"en","type":"article","venue":"","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Heuristics; Reinforcement learning; Graph; Machine learning; Maximization; Artificial intelligence; ENCODE; Social network (sociolinguistics); Theoretical computer science; Mathematical optimization; Social media","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":[0.0001090233,0.0001115013,0.0001948359,0.00006120402,0.0001521372,0.00005084481,0.00009990588,0.00002959426,0.00002940467],"category_scores_gemma":[0.00001668096,0.0001131495,0.0001071614,0.000503679,0.00002542425,0.0001034193,0.00005598127,0.0001486098,0.000001499888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000018786,"about_ca_system_score_gemma":0.000009915043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002358384,"about_ca_topic_score_gemma":0.00002462947,"domain_scores_codex":[0.9992993,0.00005273788,0.0001839848,0.0001936721,0.00006185456,0.0002084882],"domain_scores_gemma":[0.9996266,0.0001468259,0.00008239598,0.00004853509,0.00006122279,0.00003446869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003010314,0.00002693925,0.1323072,0.00001014326,0.00005980028,9.100791e-8,0.0009420157,0.7742897,0.0003511223,0.06091006,0.0003211759,0.0307516],"study_design_scores_gemma":[0.001022582,0.0001791941,0.06776094,0.0000512552,0.00009383969,9.456203e-8,0.0007482582,0.8864728,0.001438912,0.0335419,0.008058358,0.0006319321],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2515981,0.00001358415,0.7468798,0.0002521112,0.000006741648,0.0003107014,0.000001260897,0.0001047538,0.0008329494],"genre_scores_gemma":[0.9966313,0.000001773384,0.00264443,0.0001557773,0.0003798479,0.0001133915,0.00003937907,0.00001467043,0.00001940966],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7450333,"threshold_uncertainty_score":0.4614101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01655058643609039,"score_gpt":0.2885943271339991,"score_spread":0.2720437406979087,"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."}}