{"id":"W4205856092","doi":"10.1038/s41433-021-01913-3","title":"Correction to: Risk of bias: why measure it, and how?","year":2022,"lang":"en","type":"erratum","venue":"Eye","topic":"Delphi Technique in Research","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University; Impact","funders":"","keywords":"Measure (data warehouse); MEDLINE; Optometry; Computer science; Medicine; Data science; Data mining; Political science; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["metaresearch"],"domain":"methods","study_design":"not_applicable","genre":"other","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"not_applicable","genre":"other","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01980078,0.003943921,0.004384636,0.01061718,0.007163317,0.008470921,0.004655494,0.01195233,0.2017059],"category_scores_gemma":[0.3646547,0.002958486,0.002352377,0.00810454,0.00461043,0.005277713,0.004711316,0.01671132,0.1062315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006819639,"about_ca_system_score_gemma":0.01290591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01975446,"about_ca_topic_score_gemma":0.02590923,"domain_scores_codex":[0.9641187,0.01048735,0.01075643,0.002841149,0.009962287,0.001834022],"domain_scores_gemma":[0.6825473,0.08450754,0.01335624,0.02255308,0.1909877,0.006048241],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003316627,0.000006177515,0.00006389882,0.0002102554,0.000009552824,0.00008230084,0.00004983574,0.00001528722,0.00002169309,0.0004288316,0.9947631,0.004316031],"study_design_scores_gemma":[0.0001667864,0.00002263438,0.001172073,0.001789986,0.00006807714,0.0005055983,0.0004012261,0.0004304548,0.0004155125,0.003785096,0.9911384,0.0001040301],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0001857291,0.0005521948,0.002033137,0.06080573,0.9277828,0.000238524,0.003350267,0.00139734,0.003654318],"genre_scores_gemma":[0.02131602,0.004971086,0.03927056,0.1530399,0.3330494,0.004163047,0.008579813,0.01299984,0.4226103],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9801992,"threshold_uncertainty_score":0.6747735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1074508757846923,"score_gpt":0.4080716997365308,"score_spread":0.3006208239518385,"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."}}