{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001015694,0.0002419414,0.0009174173,0.0001307211,0.0001984183,0.00004569232,0.0001794646,0.00019673,0.00001356762],"category_scores_gemma":[0.00007625271,0.0001867492,0.0001164811,0.0007249142,0.00005569687,0.0001106995,0.0001085645,0.0005063842,0.000008503164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001302907,"about_ca_system_score_gemma":0.002642274,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002262242,"about_ca_topic_score_gemma":0.003087412,"domain_scores_codex":[0.996408,0.00009481755,0.002265784,0.0002146599,0.0006130272,0.0004036953],"domain_scores_gemma":[0.997844,0.0001370665,0.0007673171,0.0003608348,0.0006009376,0.0002898725],"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":[0.001711357,0.0001908459,0.5868873,0.03402473,0.00148596,0.000005769301,0.1571863,0.01408927,0.000006972038,0.0004521981,0.001361784,0.2025975],"study_design_scores_gemma":[0.0201455,0.004525926,0.09443233,0.0499905,0.001388717,0.00004162548,0.2179443,0.04942208,0.00115723,0.000001779486,0.5593948,0.001555127],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9832194,0.00412211,0.00452157,0.0004778482,0.002535994,0.002054232,0.0002432841,0.0003567479,0.002468794],"genre_scores_gemma":[0.9967769,0.0002462984,0.001187343,0.0006401425,0.00011335,0.0003569657,0.0001584846,0.00002654917,0.000493968],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.558033,"threshold_uncertainty_score":0.7615412,"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."}}