{"id":"W2364836212","doi":"10.4158/ep151042.lt","title":"Thyroid Cancer Incidence and Endocrinologist Access: A Regional Data Analysis from Ontario, Canada","year":2016,"lang":"en","type":"article","venue":"Endocrine Practice","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Cancer Care Ontario; Public Health Ontario; University of Toronto; Toronto General Hospital","funders":"","keywords":"Medicine; Thyroid cancer; Population; Incidence (geometry); Cancer; Family medicine; Cancer registry; Health care; Demography; Gerontology; Internal medicine; Environmental health; Economic growth","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001809306,0.0002153841,0.0004170733,0.00009956511,0.0001270103,0.00008030652,0.0005902587,0.00003262475,0.001573146],"category_scores_gemma":[0.001822324,0.0001501296,0.00005032491,0.0004311267,0.0001173323,0.001674498,0.000724282,0.0002958364,0.00001011471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007123392,"about_ca_system_score_gemma":0.002185867,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9972816,"about_ca_topic_score_gemma":0.9968108,"domain_scores_codex":[0.9976499,0.00008722957,0.0003386008,0.0007779258,0.0006913974,0.0004549215],"domain_scores_gemma":[0.9971533,0.0009861381,0.0002638084,0.001089719,0.0002455357,0.0002614872],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00108584,0.00006023762,0.8618674,0.00001359016,0.001775854,0.002352309,0.0001120859,0.00001529554,0.001201327,0.0002029539,0.117016,0.01429712],"study_design_scores_gemma":[0.001239607,0.0000767128,0.408246,0.0001129227,0.002277231,0.0004572245,0.0002740154,0.00007971209,0.0004391595,0.0000923031,0.5864562,0.00024893],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.830967,0.0161965,0.002630718,0.1382889,0.000450654,0.000567433,0.0007571028,0.0001426297,0.009999098],"genre_scores_gemma":[0.9823476,0.002654203,0.003434785,0.008534119,0.0003122857,0.00003640813,0.0001300108,0.0000149493,0.002535624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4694403,"threshold_uncertainty_score":0.9993396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1414091247643217,"score_gpt":0.4047521093211233,"score_spread":0.2633429845568015,"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."}}