{"id":"W4417458229","doi":"10.1111/cdoe.70046","title":"Oral Health—Head and Neck Cancers: Addressing Confounding Through Negative Control and Quantitative Bias Analyses","year":2025,"lang":"en","type":"article","venue":"Community Dentistry And Oral Epidemiology","topic":"Head and Neck Cancer Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université de Montréal; McGill University Health Centre; Centre Hospitalier de l’Université de Montréal; McGill University","funders":"Canadian Institutes of Health Research; Ministère de l'Économie, de l’Innovation et des Exportations du Québec","keywords":"Confounding; Affect (linguistics); Association (psychology); Negative control; Selection bias; Case-control study","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.327662,0.002185494,0.002171088,0.003477117,0.002000428,0.003530217,0.004081612,0.002516272,0.002424237],"category_scores_gemma":[0.4678705,0.00110211,0.006189027,0.004588601,0.004052977,0.002902018,0.004023137,0.001871741,0.0001670567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00272656,"about_ca_system_score_gemma":0.005837011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01000247,"about_ca_topic_score_gemma":0.006107954,"domain_scores_codex":[0.5292026,0.419952,0.01582755,0.01593531,0.01726944,0.001813168],"domain_scores_gemma":[0.4885094,0.4232594,0.04308939,0.02720164,0.01710714,0.0008330141],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00270616,0.0005114542,0.4992767,0.01469308,0.0495641,0.000718174,0.008610846,0.01477828,0.001569096,0.153028,0.007336449,0.2472076],"study_design_scores_gemma":[0.003251285,0.003521349,0.2595102,0.008273892,0.04201959,0.001398028,0.003562635,0.186712,0.008312291,0.4306526,0.05206567,0.0007204789],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05320932,0.01147874,0.9227812,0.003230452,0.0007114715,0.004133061,0.001507057,0.0003219442,0.002626662],"genre_scores_gemma":[0.6506028,0.002152231,0.3332109,0.001718373,0.0004245589,0.009692309,0.0008317585,0.0001078787,0.001259114],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.672338,"threshold_uncertainty_score":0.8291125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4535757169258586,"score_gpt":0.5481136108580319,"score_spread":0.09453789393217332,"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."}}