{"id":"W3122400387","doi":"10.3982/te1204","title":"Dynamics of information exchange in endogenous social networks","year":2014,"lang":"en","type":"article","venue":"Theoretical Economics","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":145,"is_retracted":false,"has_abstract":true,"ca_institutions":"Office of the Chief Medical Examiner","funders":"","keywords":"Aggregate (composite); Private information retrieval; Information exchange; Computer science; Action (physics); Social learning; Network formation; Telecommunications network; Microeconomics; Welfare; Mathematical economics; Economics; Computer network; Telecommunications","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":[0.002616777,0.00007506814,0.00022388,0.0001180144,0.00005741615,0.00005211647,0.0004420099,0.00009351123,0.0004994309],"category_scores_gemma":[0.0004747277,0.00006584886,0.00006384063,0.0001912717,0.0004583323,0.0001993036,0.0000958833,0.0001071894,0.0001795497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004484285,"about_ca_system_score_gemma":0.00001754213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004331114,"about_ca_topic_score_gemma":0.0000223383,"domain_scores_codex":[0.9988813,0.0001420371,0.0005824425,0.0001261074,0.00009573892,0.0001724082],"domain_scores_gemma":[0.9985002,0.0009330134,0.0001879244,0.0002721089,0.00005616722,0.00005053664],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002763215,0.00001872844,0.0001470551,0.000001617219,0.000001726047,3.316228e-8,0.0003968748,0.001757583,0.000003180344,0.9414817,0.00001913419,0.05614471],"study_design_scores_gemma":[0.0001764521,0.00002227784,0.0007146135,0.000001332393,0.000002763752,0.000001534491,0.0002286412,0.2026214,0.00003659741,0.7954524,0.0006819086,0.00006005063],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7474041,0.000005243267,0.1279338,0.001476498,0.0001063858,0.0001664142,0.00003250183,0.00001891912,0.1228561],"genre_scores_gemma":[0.9993512,0.000009387373,0.0002788457,0.0002453957,0.00006452617,0.00001056542,0.00001575781,0.000004708691,0.00001958776],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2519471,"threshold_uncertainty_score":0.5468418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03717421351222842,"score_gpt":0.2874504293326846,"score_spread":0.2502762158204561,"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."}}