{"id":"W4389833166","doi":"10.1002/adts.202300845","title":"Modeling and Analyzing Information Propagation Evolution Integrating Internal and External Influences","year":2023,"lang":"en","type":"article","venue":"Advanced Theory and Simulations","topic":"Opinion Dynamics and Social Influence","field":"Physics and Astronomy","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fields Institute for Research in Mathematical Sciences; York University","funders":"Fundamental Research Funds for the Central Universities; Communication University of China; Natural Science Foundation of Beijing Municipality; National Natural Science Foundation of China","keywords":"Public opinion; Computer science; Opinion leadership; Information Dissemination; Data science; Rationality; Knowledge management; Public relations; Political science; World Wide Web","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":[0.0002128035,0.0000735546,0.00007545076,0.00008605245,0.0003453832,0.00009814181,0.00002735646,0.00002143059,0.00000480661],"category_scores_gemma":[0.00004471922,0.00006902102,0.00001445465,0.0001344824,0.00004926513,0.001041547,0.00003851794,0.00008695383,0.000001811208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009477386,"about_ca_system_score_gemma":0.00001162941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003958391,"about_ca_topic_score_gemma":0.000006517738,"domain_scores_codex":[0.9995281,0.00004228448,0.0001775732,0.0000992378,0.00005660329,0.00009628016],"domain_scores_gemma":[0.9996694,0.0001247615,0.00006195372,0.0000453521,0.00006095039,0.00003763668],"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":[0.00001587274,0.000003687599,0.04654828,0.0000098405,0.00001173113,6.995801e-8,0.001858063,0.2690781,0.0006993064,0.6386421,1.287788e-7,0.0431328],"study_design_scores_gemma":[0.0001516117,0.0000109197,0.00789115,0.00004817222,0.000006662597,2.724449e-7,0.001682428,0.7342854,0.00001298814,0.255835,0.000008378155,0.00006708146],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7083842,0.00003754543,0.2913079,0.00001981181,0.00003193855,0.00007079905,0.00001290038,0.00002338109,0.0001115478],"genre_scores_gemma":[0.9991967,0.00001600166,0.0006668832,0.00001522834,0.00003792438,0.000007643106,0.00003485024,0.000003612226,0.00002114226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4652073,"threshold_uncertainty_score":0.2814596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007327435755520282,"score_gpt":0.2828584242779582,"score_spread":0.2755309885224378,"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."}}