{"id":"W4231340043","doi":"10.22360/springsim.2017.cns.015","title":"Generating Stochastic Data To Simulate a Twitter User","year":2017,"lang":"en","type":"article","venue":"","topic":"Opinion Dynamics and Social Influence","field":"Physics and Astronomy","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Recommender system; Collaborative filtering; Weibull distribution; Similarity (geometry); Cluster analysis; Information retrieval; tf–idf; Data mining; Microblogging; Social media; Term (time); World Wide Web; Machine learning; Artificial intelligence; Statistics; Mathematics","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":[0.00163966,0.0005898387,0.000542008,0.0007109864,0.0005825328,0.0006670226,0.001073744,0.001574004,0.003049678],"category_scores_gemma":[0.009219543,0.0002944031,0.0007228092,0.0008851261,0.0005773973,0.0007676628,0.000707344,0.001355533,0.0004212018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001053199,"about_ca_system_score_gemma":0.0007215539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01685311,"about_ca_topic_score_gemma":0.01298655,"domain_scores_codex":[0.9992552,0.0003244751,0.00005201122,0.0001234695,0.0001438776,0.000100839],"domain_scores_gemma":[0.9914386,0.00621813,0.0004164388,0.0005950608,0.001112847,0.0002187563],"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":[0.0002829535,0.0003018819,0.01758745,0.0001000889,0.00007201293,0.0002527977,0.0003651596,0.9524629,0.001952972,0.01848188,0.001992556,0.006147421],"study_design_scores_gemma":[0.00002832413,0.00005419017,0.001046085,0.000006003596,0.000008961017,0.00001512283,0.00005873335,0.9957818,0.00056007,0.001870882,0.0005590206,0.00001080343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9128346,0.0001213109,0.07637874,0.0007727634,0.0001508001,0.0004316193,0.003124582,0.0003918829,0.005793639],"genre_scores_gemma":[0.970159,0.00008542211,0.02557898,0.0001149884,0.0000258976,0.0004467547,0.001682457,0.00003353598,0.00187284],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01685311,"threshold_uncertainty_score":0.03350997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08011512463651256,"score_gpt":0.3680368032861803,"score_spread":0.2879216786496678,"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."}}