{"id":"W3157741034","doi":"10.1145/3449251","title":"\"Positive Energy\"","year":2021,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Misinformation; Censorship; Social media; China; Government (linguistics); Coronavirus disease 2019 (COVID-19); Public relations; Pandemic; Trustworthiness; Internet privacy; Information Dissemination; Information sharing; Business; Political science; Information overload; Medicine; Computer science","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":[0.0009093168,0.0004268861,0.0001576407,0.0008857695,0.00238842,0.002514339,0.0003550602,0.0009359773,0.008267738],"category_scores_gemma":[0.00248703,0.0001622114,0.0002755052,0.0008437201,0.003278647,0.002264141,0.003069997,0.0008363349,0.0009078805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001014571,"about_ca_system_score_gemma":0.0005754195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001663602,"about_ca_topic_score_gemma":0.003642741,"domain_scores_codex":[0.9992985,0.0002664429,0.00002906516,0.00006009554,0.0002079186,0.0001381036],"domain_scores_gemma":[0.9988012,0.0003231918,0.0002780845,0.0001316078,0.0002582385,0.0002075173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0005574404,0.0003071495,0.1616622,0.002541212,0.0003242176,0.004230928,0.2419058,0.0005893884,0.02979612,0.1463606,0.06774371,0.3439813],"study_design_scores_gemma":[0.00004012909,0.0003765839,0.2153057,0.0006747507,0.0001943115,0.002869578,0.1851128,0.001117089,0.005533788,0.02906736,0.5595531,0.0001547932],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6815305,0.001380478,0.005671085,0.009159137,0.0006310926,0.0001533209,0.0003610074,0.0002096348,0.3009038],"genre_scores_gemma":[0.9816996,0.0005381258,0.000904349,0.001487249,0.00008934342,0.00005842801,0.0001111268,0.00004132626,0.01507049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008267738,"threshold_uncertainty_score":0.02765834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0575250483566233,"score_gpt":0.3553378155702914,"score_spread":0.2978127672136681,"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."}}