{"id":"W2033477686","doi":"10.1016/j.prevetmed.2013.10.008","title":"Bias—Is it a problem, and what should we do?","year":2013,"lang":"en","type":"article","venue":"Preventive Veterinary Medicine","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Prince Edward Island","funders":"","keywords":"Confounding; Selection bias; Statistics; Sample size determination; Information bias; Observational study; Econometrics; Type I and type II errors; Publication bias; Meta-analysis; Null hypothesis; Selection (genetic algorithm); Mathematics; Computer science; Medicine; Confidence interval; Machine learning","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1518669,0.00115323,0.005902862,0.002706355,0.003750771,0.008843141,0.004528232,0.01151081,0.006540089],"category_scores_gemma":[0.3684945,0.0009111605,0.001763553,0.002457997,0.02004588,0.01585654,0.00440625,0.01115683,0.001975864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004531311,"about_ca_system_score_gemma":0.01623588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01564527,"about_ca_topic_score_gemma":0.02072255,"domain_scores_codex":[0.9078349,0.06186455,0.006203641,0.006660996,0.01516554,0.002270427],"domain_scores_gemma":[0.5794194,0.3142649,0.03277088,0.02343734,0.03775216,0.01235536],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0008826755,0.0004608137,0.1382579,0.006960186,0.004572307,0.0008295319,0.008217247,0.0006511294,0.0007132405,0.06601664,0.1517337,0.6207048],"study_design_scores_gemma":[0.0009638065,0.0008571574,0.07962141,0.03247697,0.003976072,0.004487534,0.01807884,0.0037522,0.001738577,0.5719263,0.2812781,0.0008429711],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.01060574,0.05681461,0.01072569,0.9101523,0.007382512,0.0001333772,0.0002312975,0.000179746,0.003774698],"genre_scores_gemma":[0.3582552,0.06399725,0.04249012,0.4963591,0.03247464,0.0008179242,0.0002677005,0.0004341592,0.004903913],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.8481331,"threshold_uncertainty_score":0.8031588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06515955431365139,"score_gpt":0.3140117289945521,"score_spread":0.2488521746809007,"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."}}