{"id":"W3088061996","doi":"10.3390/info11100461","title":"Bots as Active News Promoters: A Digital Analysis of COVID-19 Tweets","year":2020,"lang":"en","type":"article","venue":"Information","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Bank of Canada; Simon Fraser University","funders":"","keywords":"Internet privacy; Dissemination; Coronavirus disease 2019 (COVID-19); Mainstream; Social media; Pandemic; Incentive; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); World Wide Web; Business; Computer science; Advertising; Public relations; Political science; Medicine; Telecommunications; Virology","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":[0.001239286,0.0004764512,0.000347871,0.00460387,0.0009415089,0.00129921,0.0003246057,0.0005637758,0.001843989],"category_scores_gemma":[0.007428098,0.0002268367,0.0003308778,0.002912214,0.0004861805,0.0017846,0.0008366187,0.0006565721,0.001263918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005261477,"about_ca_system_score_gemma":0.0004516119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004112426,"about_ca_topic_score_gemma":0.006144803,"domain_scores_codex":[0.9987759,0.0003635363,0.00007807354,0.0002225693,0.000373949,0.0001858528],"domain_scores_gemma":[0.9910704,0.005124212,0.002051547,0.0005338441,0.0008598665,0.0003600871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009338289,0.000324614,0.7987524,0.001339594,0.0002751592,0.002078121,0.01555438,0.001774188,0.01976925,0.005259515,0.02383863,0.1301004],"study_design_scores_gemma":[0.00003418525,0.0002304827,0.8735307,0.0003058015,0.0002147601,0.001690239,0.01605614,0.03232323,0.005662346,0.003294454,0.06656447,0.00009312422],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9771162,0.001064777,0.004812091,0.0008122577,0.0001357057,0.0001935825,0.007440706,0.0002964495,0.008128358],"genre_scores_gemma":[0.9813855,0.0005190345,0.006003621,0.000399869,0.0001563454,0.0001944324,0.006926098,0.0001236375,0.004291562],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00460387,"threshold_uncertainty_score":0.008176982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04662423116656165,"score_gpt":0.3509413842733422,"score_spread":0.3043171531067805,"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."}}