{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002045334,0.00007719421,0.00009788381,0.00006698504,0.0003659931,0.0001724825,0.0005162564,0.00005345112,0.0002107919],"category_scores_gemma":[0.0003971955,0.00006111474,0.00009346578,0.0002128033,0.00006025434,0.0006590687,0.0002047575,0.0001235551,0.0000229848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001097296,"about_ca_system_score_gemma":0.00003766349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001236692,"about_ca_topic_score_gemma":0.00003215944,"domain_scores_codex":[0.9991862,0.00001823902,0.0001930781,0.0001242627,0.0003351902,0.0001430113],"domain_scores_gemma":[0.9991098,0.00006565449,0.000217324,0.0001523036,0.0004033837,0.00005154836],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008341153,0.0003669738,0.0004862091,0.00005801942,0.0001193456,0.000001252899,0.1070104,0.00004071359,0.0283724,0.5610867,0.2160079,0.08636669],"study_design_scores_gemma":[0.0009928031,0.0003382064,0.02121071,0.0009131097,0.00006132119,0.00003095807,0.02575879,0.0009831425,0.6672012,0.03819422,0.2437476,0.0005679591],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7521811,0.000007651038,0.0001037956,0.005892529,0.001111595,0.00009058449,0.000002031487,0.00006108931,0.2405496],"genre_scores_gemma":[0.9941159,0.00001326714,0.0005214642,0.001512737,0.0004393082,0.000001452218,0.000002096054,0.000006026729,0.00338771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6388288,"threshold_uncertainty_score":0.281496,"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."}}