{"id":"W4323529170","doi":"10.2196/44695","title":"Exploring Cancer Incidence, Risk Factors, and Mortality in the Lleida Region: Interactive, Open-source R Shiny Application for Cancer Data Analysis","year":2023,"lang":"en","type":"article","venue":"JMIR Cancer","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministerio de Economía y Competitividad; Generalitat de Catalunya; Universidad Técnica Federico Santa María","keywords":"Computer science; Population; Descriptive statistics; Analytics; Exploit; Web application; Cancer registry; Cloud computing; Data science; Database; World Wide Web; Medicine; Statistics; Computer security; Environmental health; Operating system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006241768,0.0002344379,0.0005392846,0.0002216028,0.0001612752,0.0001022977,0.0008469009,0.00005849027,0.00008431715],"category_scores_gemma":[0.0001620119,0.000169106,0.0000921445,0.001917016,0.00009231524,0.0008784052,0.0005634038,0.0002715486,0.000004475181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002830393,"about_ca_system_score_gemma":0.000237126,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05828079,"about_ca_topic_score_gemma":0.08562047,"domain_scores_codex":[0.9979034,0.0001388778,0.0003701325,0.000879303,0.0003676545,0.0003405971],"domain_scores_gemma":[0.9976255,0.0003209515,0.0002980335,0.001516176,0.0001113211,0.0001279951],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002361378,0.00005774203,0.9684955,0.0001090454,0.0005982435,0.000007376343,0.001524373,0.0005060598,0.00005282343,0.0000136943,0.007238878,0.02116014],"study_design_scores_gemma":[0.0007261555,0.00001885094,0.9139915,0.0001311598,0.0006267531,6.81647e-7,0.0009732141,0.008914143,0.0000496513,0.00003424143,0.0743429,0.0001908138],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991168,0.0009410173,0.0005673161,0.001308993,0.0001678922,0.002246353,0.003408515,0.0001042036,0.00008774677],"genre_scores_gemma":[0.981612,0.006249448,0.0000470977,0.0004084091,0.0003152061,0.009836767,0.001295029,0.00003706227,0.0001989435],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06710402,"threshold_uncertainty_score":0.9479902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2225293354513758,"score_gpt":0.4368407264154111,"score_spread":0.2143113909640353,"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."}}