{"id":"W4417506303","doi":"10.1177/00220345251392147","title":"Whose Knowledge Counts? Considering Gender, Sexuality, and Race in Description, Prediction, and Causal Inference in Oral Epidemiology","year":2025,"lang":"en","type":"article","venue":"Advances in Dental Research","topic":"Dental Health and Care Utilization","field":"Dentistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Race (biology); Causal inference; Epidemiology; Inference; Oral health; Causal model; Disease; Inequality; Corporate governance","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":[],"consensus_categories":[],"category_scores_codex":[0.001799811,0.00007710662,0.0001789173,0.0003546703,0.00006466523,0.00002590703,0.00008485522,0.0001033506,0.00003277105],"category_scores_gemma":[0.001896249,0.00008377653,0.000007095584,0.0005330986,0.0002444915,0.0002955233,0.0001982501,0.0003712012,0.00002242904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002185815,"about_ca_system_score_gemma":0.000103469,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004276248,"about_ca_topic_score_gemma":0.04156618,"domain_scores_codex":[0.9983386,0.0005379644,0.0003526684,0.0002978037,0.0001472555,0.0003257563],"domain_scores_gemma":[0.9987462,0.0009786044,0.00002721737,0.0001100053,0.00007282325,0.00006516078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005224088,0.00005256658,0.9670037,0.0002205191,0.000001440675,0.0000302786,0.0001472678,0.00002057505,0.00003439328,0.004196175,0.0001576016,0.02808326],"study_design_scores_gemma":[0.0007483409,0.00003683888,0.9729714,0.0001810096,0.000001183683,0.00002260885,0.001411527,0.001956134,0.00003942046,0.01767608,0.004888384,0.00006705747],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9726106,0.02121737,0.0004119199,0.00002400327,0.000482347,0.0002603693,0.00001284828,0.00001445765,0.004966064],"genre_scores_gemma":[0.994579,0.004358095,0.00007987977,0.00005737067,0.00001920555,0.00004386305,0.00001635045,0.000005319971,0.0008409189],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04113856,"threshold_uncertainty_score":0.9759228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.158541878319662,"score_gpt":0.5131110324055057,"score_spread":0.3545691540858437,"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."}}