{"id":"W2421567616","doi":"10.7748/ns.24.11.20.s21","title":"Discover your bias","year":2009,"lang":"en","type":"article","venue":"Nursing Standard","topic":"Social and Intergroup Psychology","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"World Federation of Science Journalists","funders":"","keywords":"Psychology; Computer science; Information retrieval; Data science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01985793,0.000600551,0.0007983039,0.002179654,0.003139215,0.003493455,0.001076725,0.003170504,0.02717157],"category_scores_gemma":[0.1528932,0.0003122459,0.0006168563,0.001301197,0.004291289,0.007299878,0.00352306,0.008482572,0.01137759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001256509,"about_ca_system_score_gemma":0.002442301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002088255,"about_ca_topic_score_gemma":0.003824969,"domain_scores_codex":[0.9905093,0.003353018,0.0004444406,0.0009693571,0.004065518,0.0006584167],"domain_scores_gemma":[0.9229256,0.03817391,0.005380297,0.009548412,0.01851781,0.005454038],"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":[0.000080033,0.0001076343,0.01697975,0.0001695422,0.0001108002,0.0001861567,0.003314754,0.00004319833,0.0008038169,0.03771313,0.7486432,0.191848],"study_design_scores_gemma":[0.00008241284,0.00011202,0.01158952,0.0007421058,0.000102265,0.0008133848,0.007448889,0.0005925813,0.002359252,0.1629762,0.8131039,0.00007762849],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.01599627,0.007847678,0.01303314,0.8663155,0.04570405,0.00006540475,0.0003564227,0.0004059616,0.05027559],"genre_scores_gemma":[0.2306486,0.01155803,0.02713518,0.5458524,0.04021741,0.0003705304,0.0006798421,0.001194396,0.1423435],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02717157,"threshold_uncertainty_score":0.10502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07947624432380013,"score_gpt":0.4312553564519125,"score_spread":0.3517791121281124,"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."}}