{"id":"W3109231514","doi":"10.3390/info11110539","title":"Addressing Misinformation in Online Social Networks: Diverse Platforms and the Potential of Multiagent Trust Modeling","year":2020,"lang":"en","type":"article","venue":"Information","topic":"Access Control and Trust","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Misinformation; Computer science; Trustworthiness; Internet privacy; Order (exchange); Data science; Reflection (computer programming); Collective intelligence; World Wide Web; Computer security; Business","routes":{"ca_aff":true,"ca_fund":true,"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":[0.009847503,0.0007366907,0.0008306614,0.002466851,0.001800685,0.005249645,0.001589762,0.002428556,0.001133774],"category_scores_gemma":[0.04745381,0.0004753536,0.000814298,0.001627693,0.002813854,0.01077798,0.003241174,0.002307055,0.0002294866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001668413,"about_ca_system_score_gemma":0.0009703477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00439331,"about_ca_topic_score_gemma":0.003780393,"domain_scores_codex":[0.9931479,0.004731795,0.0002757158,0.0006338043,0.0009157778,0.0002949227],"domain_scores_gemma":[0.9546884,0.03194882,0.006093156,0.00375183,0.002445865,0.001071991],"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":[0.0004540456,0.0003254229,0.08909348,0.0004439083,0.000675395,0.00164423,0.01477082,0.2936918,0.003296379,0.4392933,0.002732655,0.1535786],"study_design_scores_gemma":[0.0000183425,0.0001099531,0.005853951,0.0001192862,0.00008992988,0.0003302162,0.003071592,0.7374427,0.001082445,0.2477436,0.004056942,0.00008108527],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3295493,0.002204774,0.6411621,0.01148905,0.000167841,0.0002006085,0.0001731124,0.0002412188,0.01481199],"genre_scores_gemma":[0.9659963,0.0004306083,0.03245268,0.0001494671,0.00007357101,0.00004175026,0.00003282426,0.0000162954,0.0008064471],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009847503,"threshold_uncertainty_score":0.0520792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06008268616445651,"score_gpt":0.3023274843960031,"score_spread":0.2422447982315466,"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."}}