{"id":"W4403093192","doi":"10.37016/mr-2020-159","title":"Misinformed about misinformation: On the polarizing discourse on misinformation and its consequences for the field","year":2024,"lang":"en","type":"article","venue":"Harvard Kennedy School Misinformation Review","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Misinformation; Field (mathematics); Psychology; Political science; Law; Mathematics","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":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004623147,0.0004385144,0.0004127956,0.0002883621,0.002438601,0.002295078,0.0007080744,0.0002220037,0.002423662],"category_scores_gemma":[0.007033668,0.0002534183,0.0003082911,0.000865027,0.000278517,0.005574763,0.00005683355,0.0005880531,0.003898034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002423281,"about_ca_system_score_gemma":0.0007367414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000710016,"about_ca_topic_score_gemma":0.00004222639,"domain_scores_codex":[0.9962046,0.0001765733,0.001443164,0.0002296417,0.001260101,0.0006859503],"domain_scores_gemma":[0.9949002,0.003125586,0.0005691737,0.0005595995,0.0004625175,0.0003829229],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009263552,0.00001957709,0.000003435698,0.002486095,0.0001107967,9.66054e-7,0.01762856,0.00009025371,0.000007181513,0.4077407,0.421832,0.1499878],"study_design_scores_gemma":[0.0003760684,0.0001703943,0.0001782451,0.004732852,0.0001203355,0.00001825744,0.007257714,0.006632246,0.0001824067,0.000493107,0.979443,0.0003954263],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.006738513,0.04576511,0.009587137,0.4157862,0.005795924,0.01927021,0.0004456123,0.001432677,0.4951786],"genre_scores_gemma":[0.4320333,0.2758832,0.0005679986,0.2762501,0.001924297,0.0006763053,0.0006156082,0.0001051177,0.01194405],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.557611,"threshold_uncertainty_score":0.9999918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04532339037508426,"score_gpt":0.3744387492576136,"score_spread":0.3291153588825294,"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."}}