{"id":"W1765349666","doi":"10.48550/arxiv.1307.4047","title":"Convex relaxation for finding planted influential nodes in a social network","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Bipartite graph; Relaxation (psychology); Generative model; Regular polygon; Probabilistic logic; Computer science; Graphical model; Set (abstract data type); Mathematical optimization; Theoretical computer science; Time complexity; Graph; Mathematics; Generative grammar; Algorithm; Artificial intelligence","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001900003,0.0002648775,0.0004375124,0.0002109742,0.0002111532,0.00007646542,0.0003856091,0.0002057638,0.0002141936],"category_scores_gemma":[0.00000539908,0.0003351509,0.0003138572,0.0003745865,0.00005941989,0.0001338699,0.0004405676,0.0004512224,0.00001856055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001407256,"about_ca_system_score_gemma":0.00007694335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006983447,"about_ca_topic_score_gemma":0.00007230195,"domain_scores_codex":[0.9986296,0.0000986914,0.0002734743,0.0005777336,0.0000518978,0.0003685464],"domain_scores_gemma":[0.9990219,0.0001188798,0.0004171627,0.000282273,0.00010786,0.0000519403],"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":[0.0001866492,0.0001726904,0.2394748,0.00008765118,0.0006101732,0.00001130696,0.0003848266,0.3144944,0.00005473498,0.433068,0.009415855,0.002038991],"study_design_scores_gemma":[0.001187184,0.00002630902,0.01563931,0.0002119172,0.0003336207,1.495029e-7,0.0001742944,0.5533709,0.00006902718,0.4267005,0.001553336,0.0007334592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7753953,0.0000111841,0.2219904,0.00002138269,0.000136858,0.0005833979,0.00004577714,0.0001008232,0.001714859],"genre_scores_gemma":[0.9976355,0.000006159564,0.0005951455,0.00001811817,0.0008016503,0.00001457393,0.0004181702,0.00002664621,0.0004840158],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2388765,"threshold_uncertainty_score":0.9999101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06340286974963392,"score_gpt":0.2205110240657553,"score_spread":0.1571081543161214,"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."}}