{"id":"W4290600861","doi":"10.3390/healthcare10081475","title":"Health-Related Rumor Control through Social Collaboration Models: Lessons from Cases in China during the COVID-19 Pandemic","year":2022,"lang":"en","type":"article","venue":"Healthcare","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Sichuan University","keywords":"Rumor; Government (linguistics); Public relations; Credibility; Social media; Public health; Socialization; Pandemic; Distrust; Political science; Sociology; Internet privacy; Computer science; Data science; Psychology; Coronavirus disease 2019 (COVID-19); Social psychology; 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":["sts"],"consensus_categories":[],"category_scores_codex":[0.001594306,0.0001037378,0.0002375217,0.00006907059,0.004323847,0.00008284362,0.0002132327,0.0000847497,0.00035898],"category_scores_gemma":[0.000398004,0.00009335519,0.00004460899,0.00075554,0.00009827652,0.0004487726,0.00004300707,0.0004191393,0.000008218696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002041733,"about_ca_system_score_gemma":0.002910455,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1583507,"about_ca_topic_score_gemma":0.1104023,"domain_scores_codex":[0.9964784,0.00188392,0.0004647812,0.0001829533,0.0005484378,0.0004414413],"domain_scores_gemma":[0.9990318,0.0002769533,0.0002914673,0.0001364716,0.00005503253,0.0002082885],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002364255,0.00005422173,0.01062461,0.00008775138,0.00001562946,0.00001644772,0.9050933,0.006617105,0.000005723216,0.0698392,0.005627825,0.001781777],"study_design_scores_gemma":[0.005748556,0.000195624,0.141579,0.00005066234,0.00001385876,0.00004605868,0.7349622,0.004800885,0.000001468174,0.04369693,0.06838185,0.0005229057],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6958553,0.0009726936,0.00007004476,0.300054,0.0003005468,0.0008699055,0.0006954632,0.0001340164,0.001048096],"genre_scores_gemma":[0.9870121,0.0003083758,0.00001093534,0.01226287,0.0001088595,0.00004912675,0.00009383652,0.00001022635,0.0001436888],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2911569,"threshold_uncertainty_score":0.9969724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1298038895908917,"score_gpt":0.4191768799179748,"score_spread":0.2893729903270831,"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."}}