{"id":"W3124586607","doi":"10.1561/2000000048","title":"Interactive Sensing and Decision Making in Social Networks","year":2014,"lang":"en","type":"article","venue":"Foundations and Trends® in Signal Processing","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Stylized fact; Computer science; Variety (cybernetics); Social media; Data science; Reputation; Microblogging; Social network analysis; Social network (sociolinguistics); Management science; Artificial intelligence; World Wide Web; Social science; Engineering; Sociology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005157592,0.0009631283,0.001162826,0.001343027,0.001242784,0.004374855,0.001560608,0.002521838,0.002997946],"category_scores_gemma":[0.0201102,0.0008051436,0.001110499,0.001542093,0.00574016,0.005672702,0.002881705,0.002188321,0.0003570151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002086887,"about_ca_system_score_gemma":0.001270482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00381368,"about_ca_topic_score_gemma":0.002920605,"domain_scores_codex":[0.994329,0.003254277,0.0002007853,0.001100877,0.0007697843,0.00034526],"domain_scores_gemma":[0.9755617,0.02135968,0.001458759,0.000755908,0.0004799821,0.000383982],"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":[0.00004913229,0.00005348224,0.001517394,0.0002318822,0.0001054086,0.0002757554,0.0007829761,0.1456905,0.0009477675,0.8300432,0.001198142,0.01910432],"study_design_scores_gemma":[0.00001291522,0.00002183547,0.0004763424,0.00004107503,0.00001713203,0.00006027392,0.0001492719,0.2136157,0.0002713458,0.7830554,0.002253603,0.00002500099],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05213045,0.002913675,0.9156486,0.006628468,0.0001344378,0.0001356501,0.0002690065,0.0001404083,0.02199938],"genre_scores_gemma":[0.8913293,0.00349788,0.09920806,0.0005769837,0.0002970533,0.0003188705,0.0001417867,0.0000433211,0.004586637],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005157592,"threshold_uncertainty_score":0.02727628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06437555810217523,"score_gpt":0.4102390331691072,"score_spread":0.345863475066932,"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."}}