{"id":"W2951988542","doi":"10.1007/s11013-019-09635-8","title":"Ebola and Localized Blame on Social Media: Analysis of Twitter and Facebook Conversations During the 2014–2015 Ebola Epidemic","year":2019,"lang":"en","type":"article","venue":"Culture Medicine and Psychiatry","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":95,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; University of Ottawa","funders":"Institut National de la Santé et de la Recherche Médicale","keywords":"Blame; Social media; Public health; Social psychology; Sociology; Meaning (existential); Political science; Psychology; Criminology; Public relations; Medicine; Law","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":[0.0005997788,0.0001050557,0.0002891177,0.0001220422,0.0003118598,0.00002473972,0.00007549967,0.0001156213,0.0005475744],"category_scores_gemma":[0.0001398655,0.00006008586,0.00004528497,0.0002504548,0.0004422058,0.0001104292,0.00001675668,0.0001605629,0.00001155498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001168673,"about_ca_system_score_gemma":0.00004519791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001312785,"about_ca_topic_score_gemma":0.0003660243,"domain_scores_codex":[0.9990891,0.0001228643,0.0002351758,0.000133346,0.0002696387,0.0001499373],"domain_scores_gemma":[0.9994102,0.0001580086,0.0001542806,0.0001008797,0.0000582764,0.0001183136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001077071,0.00002799209,0.05122171,0.000127195,0.0005144886,3.635746e-7,0.6803283,0.000005182678,0.0003719204,0.01989181,0.2458609,0.001542392],"study_design_scores_gemma":[0.004967574,0.0001632915,0.3696668,0.0002128985,0.001456165,0.000005312985,0.3685207,0.0002885126,0.0000290105,0.002492798,0.2517899,0.0004069891],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9492372,0.001145585,0.00002626502,0.02813983,0.0004505448,0.0003450664,0.0000132814,0.00002058412,0.02062158],"genre_scores_gemma":[0.9937435,0.000994225,0.0000291526,0.003028619,0.0003700222,0.000002329014,0.00001313977,0.000004359927,0.001814634],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3184451,"threshold_uncertainty_score":0.5995556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02919872503105597,"score_gpt":0.3356542733195396,"score_spread":0.3064555482884836,"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."}}