{"id":"W4310973929","doi":"10.31234/osf.io/qy94s","title":"High level of correspondence across different news domain quality rating sets","year":2022,"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","funders":"Social Sciences and Humanities Research Council of Canada; Volkswagen Foundation; Alexander von Humboldt-Stiftung; John Templeton Foundation","keywords":"Misinformation; Computer science; Quality (philosophy); Aggregate (composite); Reliability (semiconductor); Set (abstract data type); Domain (mathematical analysis); Information retrieval; Data science; Mathematics; 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":[0.032616,0.0007333216,0.001225741,0.005604554,0.0008796742,0.003039641,0.0007632883,0.001218575,0.003056903],"category_scores_gemma":[0.2022624,0.0004061172,0.0009409465,0.00435485,0.00104957,0.002333145,0.002789091,0.001710231,0.001374163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006943319,"about_ca_system_score_gemma":0.0004987044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001776595,"about_ca_topic_score_gemma":0.001759937,"domain_scores_codex":[0.9626008,0.01484922,0.003636035,0.006851145,0.01110131,0.0009614639],"domain_scores_gemma":[0.7135004,0.2048251,0.01562459,0.02962337,0.03453401,0.001892494],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001766091,0.0006282912,0.721347,0.001692004,0.003252927,0.0005527097,0.01115209,0.0144537,0.01322862,0.009373466,0.01475582,0.2077973],"study_design_scores_gemma":[0.0001083231,0.0004424699,0.9107047,0.0002686115,0.0005216845,0.0006467492,0.002269716,0.04496161,0.007702691,0.01620092,0.0158938,0.0002787125],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8427259,0.00147965,0.1266952,0.0005025237,0.0003368162,0.0008848134,0.005596341,0.0008092455,0.0209695],"genre_scores_gemma":[0.974696,0.0001990983,0.01799629,0.0001355349,0.00008690098,0.0003089163,0.0051937,0.0001823357,0.001201171],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.032616,"threshold_uncertainty_score":0.172492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2596519952068824,"score_gpt":0.4685832607038062,"score_spread":0.2089312654969238,"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."}}