{"id":"W4412788639","doi":"10.2196/75022","title":"Deep Learning and Image Generator Health Tabular Data (IGHT) for Predicting Overall Survival in Patients With Colorectal Cancer: Retrospective Study","year":2025,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Colorectal cancer; Medicine; Computer science; Cancer; Artificial intelligence; World Wide Web; Internal medicine","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":[0.002160947,0.0003274507,0.0003900539,0.001241952,0.0002451111,0.000620485,0.0005098925,0.0005149475,0.00107213],"category_scores_gemma":[0.006978984,0.000238365,0.0007383195,0.001111329,0.0003575859,0.0007187459,0.0005909841,0.0007073079,0.0004190858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006387046,"about_ca_system_score_gemma":0.0005342603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005437109,"about_ca_topic_score_gemma":0.004242184,"domain_scores_codex":[0.9990884,0.0003052819,0.00009421104,0.0002339129,0.0001683621,0.0001097547],"domain_scores_gemma":[0.9957951,0.001568096,0.0009608283,0.0006943537,0.0006647067,0.0003168344],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004378905,0.00008219505,0.9938113,0.00002545055,0.0001038999,0.00009925978,0.00004270311,0.0006555773,0.0001308485,0.00003647717,0.0003232097,0.004251189],"study_design_scores_gemma":[0.0000744896,0.000854659,0.9725317,0.00005251379,0.000322294,0.0009258537,0.0003833751,0.02230192,0.0007263987,0.0002447478,0.001552203,0.00002984719],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969331,0.0003374669,0.0008417476,0.00006613536,0.000007900499,0.00003134237,0.001524458,0.00001157014,0.0002463062],"genre_scores_gemma":[0.9974239,0.0001219267,0.0003956892,0.00003146607,0.000009471914,0.00002418535,0.001859668,0.00000497481,0.0001287426],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005437109,"threshold_uncertainty_score":0.01142836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01035878681444719,"score_gpt":0.300030831740718,"score_spread":0.2896720449262709,"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."}}