{"id":"W4416987187","doi":"10.2196/79011","title":"FHIR Standard–Based Oncology Data Model for Cancer Screening: Design and Implementation Study","year":2025,"lang":"en","type":"article","venue":"JMIR Cancer","topic":"AI in cancer detection","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Interoperability; Cancer; Data sharing; Health data; Work (physics); Data exchange; Focus (optics); Patient data; Survivorship curve","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01892214,0.0005857177,0.0003565379,0.001121442,0.0006312507,0.001861138,0.002225667,0.0009118158,0.005753844],"category_scores_gemma":[0.02518121,0.0005159779,0.000976256,0.0009757571,0.0006734466,0.002258131,0.001792884,0.001142596,0.0007952796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003793032,"about_ca_system_score_gemma":0.0070424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01608564,"about_ca_topic_score_gemma":0.008788549,"domain_scores_codex":[0.9922333,0.004954144,0.0005571957,0.0006363356,0.00116702,0.0004520263],"domain_scores_gemma":[0.9835633,0.008002197,0.0007973862,0.001798703,0.005190141,0.0006482098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00658991,0.01267135,0.1353999,0.003140038,0.000506115,0.001077365,0.005294865,0.2177161,0.01817128,0.1198041,0.03321501,0.446414],"study_design_scores_gemma":[0.001877372,0.006334798,0.02554053,0.0006164763,0.0005435483,0.0003282964,0.004112445,0.8665637,0.02399551,0.01324205,0.05663615,0.0002090681],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4230537,0.0002662895,0.5245973,0.001634448,0.0001878365,0.0242334,0.005462659,0.004164929,0.01639935],"genre_scores_gemma":[0.4317341,0.0001481212,0.5476655,0.0003619878,0.00001954852,0.0122161,0.004970093,0.0002287758,0.002655688],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01892214,"threshold_uncertainty_score":0.100071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.148279432940168,"score_gpt":0.4809391055522493,"score_spread":0.3326596726120813,"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."}}