{"id":"W2994760291","doi":"10.1002/ijc.32837","title":"Arsenic and gallbladder cancer risk: Mendelian randomization analysis of European prospective data","year":2019,"lang":"en","type":"letter","venue":"International Journal of Cancer","topic":"Nitrogen and Sulfur Effects on Brassica","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Cancer Research","funders":"Seventh Framework Programme; World Health Organization; Bundesministerium für Bildung und Forschung; Universität Heidelberg; European Commission; Deutsche Forschungsgemeinschaft","keywords":"Mendelian randomization; Gallbladder cancer; Medicine; Arsenic; Prospective cohort study; Randomization; Internal medicine; Oncology; Cancer; Biology; Clinical trial; Genetics; Chemistry; Gene; Genotype","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":[0.0415656,0.001034742,0.002339985,0.001823787,0.0004059588,0.001276481,0.00238002,0.002772309,0.002821487],"category_scores_gemma":[0.1834517,0.0007705894,0.002377909,0.002943267,0.001182439,0.0008918636,0.0006591119,0.002492383,0.0004544285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005377349,"about_ca_system_score_gemma":0.0007652934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001132601,"about_ca_topic_score_gemma":0.0009924618,"domain_scores_codex":[0.9683833,0.02379677,0.002700712,0.002214636,0.002575855,0.000328684],"domain_scores_gemma":[0.859426,0.1143283,0.01368311,0.006767482,0.005103901,0.0006911383],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0177096,0.0003831295,0.2675477,0.007908994,0.04795308,0.01085159,0.0007678255,0.004187803,0.001135076,0.008118466,0.4317792,0.2016576],"study_design_scores_gemma":[0.01195671,0.0063596,0.4046737,0.01033009,0.05246936,0.02862005,0.0007732013,0.1042959,0.0041603,0.05302669,0.3221344,0.001199958],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3203766,0.1491015,0.1002215,0.2667722,0.1419187,0.001202572,0.01455305,0.001703552,0.004150283],"genre_scores_gemma":[0.7904839,0.02794594,0.04297335,0.04732716,0.08247766,0.001644065,0.002725669,0.0006507333,0.003771469],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0415656,"threshold_uncertainty_score":0.2198225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01095182007526789,"score_gpt":0.3014456447683371,"score_spread":0.2904938246930692,"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."}}