{"id":"W4391636380","doi":"10.31234/osf.io/u8anb","title":"Reducing misinformation sharing at scale using digital accuracy prompt ads","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina; Kellogg's (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Misinformation; Psychological intervention; Computer science; Scale (ratio); Internet privacy; Intervention (counseling); Psychology; Computer security","routes":{"ca_aff":true,"ca_fund":true,"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":[0.009658273,0.000809786,0.0008309005,0.0009247965,0.0009562775,0.001642077,0.000863826,0.001384176,0.01441592],"category_scores_gemma":[0.05093409,0.0003443217,0.001252285,0.0005629464,0.001260432,0.002130704,0.001671893,0.001953597,0.001093077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009023869,"about_ca_system_score_gemma":0.001790917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001393439,"about_ca_topic_score_gemma":0.001402273,"domain_scores_codex":[0.9909831,0.006391223,0.0004618343,0.0005534319,0.001262812,0.0003475678],"domain_scores_gemma":[0.9634473,0.0278863,0.003947916,0.002086468,0.001236636,0.00139533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.05548549,0.08517219,0.0167786,0.01276814,0.002698325,0.0002402076,0.005165554,0.002877014,0.01235129,0.005921817,0.01092826,0.789613],"study_design_scores_gemma":[0.1418994,0.4197908,0.2217774,0.009864348,0.01065166,0.0006742895,0.007510007,0.01461859,0.0442654,0.03464999,0.09356942,0.000728579],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9476776,0.003417196,0.01040166,0.00426865,0.001099741,0.009878742,0.000885667,0.0008657984,0.02150485],"genre_scores_gemma":[0.971814,0.001709252,0.01419264,0.001921959,0.0004490541,0.006893391,0.0002634069,0.00006131644,0.002695057],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01441592,"threshold_uncertainty_score":0.05107844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06972233958247405,"score_gpt":0.3692027411552911,"score_spread":0.2994804015728171,"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."}}