{"id":"W4416786470","doi":"10.2196/72665","title":"Comparison of Machine Learning Models for Colon Cancer Survival: Predictive Modeling Approach","year":2025,"lang":"en","type":"article","venue":"JMIR Cancer","topic":"AI in cancer detection","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute","keywords":"Colorectal cancer; Predictive modelling; Cancer; Clinical Practice; MEDLINE","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":[0.000265183,0.0001858385,0.0004020742,0.0001646244,0.0001844682,0.00004782448,0.0005655827,0.0001243875,0.000006636746],"category_scores_gemma":[0.00001641728,0.0001863638,0.0001087729,0.0005903853,0.00004514462,0.0004025261,0.0001898954,0.0002930898,3.888267e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004630424,"about_ca_system_score_gemma":0.0003156354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001322418,"about_ca_topic_score_gemma":0.0003151269,"domain_scores_codex":[0.9984004,0.00007419286,0.000379579,0.0005346477,0.0003035607,0.0003075601],"domain_scores_gemma":[0.9989871,0.00009970853,0.0002144992,0.0003402947,0.0003088344,0.00004959207],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001338744,0.00006652174,0.002657475,0.000184444,0.00008062122,6.910341e-8,0.001313627,0.9685196,0.0004660983,0.003602583,0.0004837893,0.02249133],"study_design_scores_gemma":[0.0006348244,0.0001081341,0.0001009516,0.0001176332,0.00003047702,1.713081e-7,0.0001180927,0.9923699,0.002464843,0.002281928,0.001609121,0.0001638688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008312409,0.003052043,0.9841564,0.0003364067,0.0009924986,0.0008725825,0.00003726819,0.0001986214,0.002041715],"genre_scores_gemma":[0.9857615,0.0001874685,0.01099685,0.00007980517,0.0001211436,0.002238821,0.000006420135,0.00002139819,0.0005866553],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.977449,"threshold_uncertainty_score":0.7599694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.104072846837206,"score_gpt":0.3836249451323374,"score_spread":0.2795520982951314,"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."}}