{"id":"W4414497914","doi":"10.1200/cci-25-00073","title":"Development of Machine Learning Systems to Predict Cancer-Related Symptoms With Validation Across a Health Care System","year":2025,"lang":"en","type":"article","venue":"JCO Clinical Cancer Informatics","topic":"Cancer survivorship and care","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sunnybrook Health Science Centre; Vector Institute; Institute for Clinical Evaluative Sciences; Princess Margaret Cancer Centre; Ontario Institute for Cancer Research; University of Toronto; University Health Network","funders":"","keywords":"Health care; Healthcare system; MEDLINE; Patient care; Cancer","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02234765,0.001315402,0.001050027,0.002320854,0.0005150938,0.001702551,0.001311655,0.0009603186,0.0007821509],"category_scores_gemma":[0.05383893,0.000586842,0.001756459,0.001363454,0.0004241647,0.001435387,0.0009940469,0.001401392,0.0002963532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001582199,"about_ca_system_score_gemma":0.001929108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01404861,"about_ca_topic_score_gemma":0.01223412,"domain_scores_codex":[0.992463,0.004725411,0.0006349784,0.001187816,0.0008094905,0.0001793023],"domain_scores_gemma":[0.9668809,0.02516237,0.002455818,0.001883812,0.003350957,0.0002660674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008700974,0.0008128419,0.4575785,0.001110077,0.00663371,0.0002037534,0.0003236797,0.2928466,0.003539216,0.000949687,0.004499962,0.230632],"study_design_scores_gemma":[0.0002052802,0.001520402,0.06740892,0.000369442,0.001838374,0.0001671093,0.0001737356,0.917839,0.004847657,0.002485025,0.00306015,0.00008483345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6955701,0.01058668,0.2742294,0.00404642,0.0004542815,0.001528655,0.00507581,0.003563511,0.004945061],"genre_scores_gemma":[0.9213348,0.0007368263,0.07423102,0.0006062331,0.00008655509,0.0003314213,0.002270729,0.00005202697,0.0003504001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02234765,"threshold_uncertainty_score":0.1181871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03125883889986466,"score_gpt":0.3952493086010034,"score_spread":0.3639904697011388,"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."}}