{"id":"W4388488996","doi":"10.25046/aj080507","title":"Modeling Control Agents in Social Media Networks Using Reinforcement Learning","year":2023,"lang":"en","type":"article","venue":"Advances in Science Technology and Engineering Systems Journal","topic":"Opinion Dynamics and Social Influence","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Reinforcement learning; Computer science; Control (management); Reinforcement; Social learning; Artificial intelligence; Psychology; Social psychology; Knowledge management","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":[0.0007682078,0.00008598923,0.0001683585,0.000849215,0.0003145944,0.00006424454,0.0001763339,0.00005821466,0.000001139839],"category_scores_gemma":[0.00004101329,0.00008646496,0.0000179596,0.001630472,0.0001155906,0.0004186082,0.00005064039,0.0004618186,6.357853e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007116292,"about_ca_system_score_gemma":0.00003458291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001261338,"about_ca_topic_score_gemma":0.000001294131,"domain_scores_codex":[0.9990575,0.00001200536,0.0002771901,0.0001393088,0.0001414078,0.0003725818],"domain_scores_gemma":[0.9997801,0.00003216983,0.0000686232,0.00004457388,0.00003868513,0.00003582947],"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":[0.000001166825,0.000002167804,0.03258634,0.000004332872,0.000002422965,0.000004199607,0.0002214098,0.9443916,0.0001188253,0.02159353,1.540229e-7,0.001073854],"study_design_scores_gemma":[0.0002654308,0.000006652648,0.0007192689,0.0001037431,0.00000145344,0.000005384491,0.00118464,0.9964645,0.000001741447,0.001100389,0.00005816837,0.00008866261],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.80345,0.0004442629,0.1952806,0.00002232515,0.0006277079,0.00006072622,4.083737e-7,0.00004000192,0.00007397531],"genre_scores_gemma":[0.9996231,0.0001022927,0.0001084938,0.000002536135,0.0001464203,0.000007535612,4.134062e-7,0.000005862912,0.000003392985],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1961731,"threshold_uncertainty_score":0.3525939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01519384097658011,"score_gpt":0.2918902583948212,"score_spread":0.2766964174182411,"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."}}