{"id":"W3160881857","doi":"10.3332/ecancer.2021.1229","title":"Differences in cancer incidence and pattern between urban and rural Nepal: one-year experience from two population-based cancer registries","year":2021,"lang":"en","type":"article","venue":"ecancermedicalscience","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Ministry of Health and Population","keywords":"Medicine; Cancer; Cancer registry; Incidence (geometry); Rural area; Population; Demography; Cancer incidence; Demographics; Cancer prevention; Cervix; Environmental health; Pathology; Internal medicine","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":[0.0002559369,0.0002473716,0.0005753876,0.000097241,0.0002089874,0.0001147145,0.0002527045,0.0001148178,0.000377606],"category_scores_gemma":[0.0004646642,0.0002227821,0.00004380362,0.0007014506,0.0008299728,0.0003773411,0.000158239,0.0003513866,0.000002252206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002949195,"about_ca_system_score_gemma":0.000934634,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0684612,"about_ca_topic_score_gemma":0.01492377,"domain_scores_codex":[0.997172,0.0000830418,0.0004697329,0.0007658559,0.0009747713,0.0005345952],"domain_scores_gemma":[0.9986175,0.0002972503,0.0001719,0.0003327593,0.000139253,0.0004413178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003735437,0.00001653987,0.9712034,0.00003895669,0.00001069552,0.00004214996,0.001052215,0.000009950485,0.0004283158,0.00003064349,0.0001007504,0.02702896],"study_design_scores_gemma":[0.001134514,0.00006945689,0.9923562,0.001735938,0.00004501853,0.000004364129,0.00101672,0.001895598,0.0009639546,0.0002308442,0.0002838334,0.0002635495],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9862995,0.008309895,0.0003757461,0.004328981,0.0002437153,0.0002034336,0.0001085482,0.00006154017,0.00006863106],"genre_scores_gemma":[0.9953991,0.001534685,0.0005499093,0.00184341,0.0004647729,0.0001068205,0.00002553147,0.00001655437,0.00005927531],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05353744,"threshold_uncertainty_score":0.937742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0767123884886184,"score_gpt":0.368605326920166,"score_spread":0.2918929384315476,"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."}}