{"id":"W3127933676","doi":"10.3390/healthcare9020156","title":"Web Search Engine Misinformation Notifier Extension (SEMiNExt): A Machine Learning Based Approach during COVID-19 Pandemic","year":2021,"lang":"en","type":"article","venue":"Healthcare","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Misinformation; Computer science; Artificial intelligence; Web search query; Search engine; Information retrieval; Machine learning; World Wide Web; Computer security","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":[0.001559409,0.0001370408,0.0001934407,0.0001942893,0.001359271,0.0001453692,0.0001307232,0.0001861369,0.000655235],"category_scores_gemma":[0.001734591,0.0001359452,0.00007139417,0.0006919505,0.00006343977,0.0005077315,0.00004400548,0.0004817845,0.00007981968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005339403,"about_ca_system_score_gemma":0.001923292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0014095,"about_ca_topic_score_gemma":0.0009061957,"domain_scores_codex":[0.9976927,0.0004446239,0.0003864352,0.0002167502,0.0007337798,0.0005256925],"domain_scores_gemma":[0.9984647,0.0001517245,0.0001217505,0.0002279406,0.000331372,0.0007025251],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006125761,0.0004120482,0.1348025,0.007798297,0.00007037054,0.0001247905,0.6168857,0.08280341,0.004615853,0.006836773,0.006891666,0.138146],"study_design_scores_gemma":[0.005264066,0.00015248,0.03446299,0.0003636661,0.00002994059,0.0001653761,0.134674,0.4771448,0.001164056,0.00009364285,0.3453572,0.001127724],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9510289,0.001217344,0.008086318,0.02156369,0.0003723259,0.0008285848,0.00005708964,0.0007145535,0.01613122],"genre_scores_gemma":[0.9924846,0.0004421188,0.0008365257,0.003307423,0.0001489739,0.000005130526,0.0003292577,0.00001442838,0.002431557],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4822116,"threshold_uncertainty_score":0.9999408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1096771282038783,"score_gpt":0.3831739194392211,"score_spread":0.2734967912353428,"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."}}