{"id":"W4383224380","doi":"10.1158/1055-9965.23627266.v1","title":"Supplementary Figure 1 from Site-Specific Cancer Incidence by Race and Immigration Status in Canada 2006–2015: A Population-Based Data Linkage Study","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Demography; Race (biology); Cancer incidence; Immigration; Incidence (geometry); Linkage (software); Population; Cancer; Record linkage; Geography; Genealogy; Medicine; Genetics; History; Biology; Sociology; Mathematics; Internal medicine; Gender studies; Gene","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00170886,0.001120418,0.001194383,0.005042818,0.002519556,0.003028501,0.002184198,0.0008663978,0.5628685],"category_scores_gemma":[0.03818101,0.0008285563,0.001399295,0.01577426,0.0005230261,0.001379668,0.001682019,0.001215386,0.07146215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006036706,"about_ca_system_score_gemma":0.02076535,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7497736,"about_ca_topic_score_gemma":0.8204721,"domain_scores_codex":[0.9974654,0.0002190573,0.0003725496,0.0005464129,0.0009748446,0.0004217945],"domain_scores_gemma":[0.9700927,0.008449046,0.002177233,0.00204974,0.01528266,0.001948613],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00004657576,0.00001835611,0.005414133,0.0004378797,0.0000558834,0.00003450578,0.0000556598,0.0001193326,0.00001834134,0.000322288,0.9903781,0.003098964],"study_design_scores_gemma":[0.001121178,0.0000510191,0.1565752,0.002480129,0.0002903079,0.0004821975,0.000829272,0.0008467003,0.0002344986,0.002210836,0.8347451,0.0001335487],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003679224,0.00004055051,0.0001413803,0.0001326122,0.0001056201,0.00004981646,0.9976591,0.0001049595,0.001398064],"genre_scores_gemma":[0.008107057,0.0002660185,0.001859993,0.0004302871,0.0001385219,0.0005990801,0.9792736,0.0003752909,0.0089502],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5628685,"threshold_uncertainty_score":0.623515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0836597241662136,"score_gpt":0.3570009020238576,"score_spread":0.2733411778576441,"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."}}