{"id":"W4414350165","doi":"10.1158/1538-7445.ovarian25-a016","title":"Abstract A016: Empowering ovarian cancer patients using CancerStop: A webapp for integrating survivorship data, clinical trials, and more features for improved outcomes","year":2025,"lang":"en","type":"article","venue":"Cancer Research","topic":"Cardiovascular Health and Risk Factors","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"3v Geomatics (Canada)","funders":"","keywords":"Survivorship curve; Personalized medicine; Scalability; Clinical trial; Precision medicine; JavaScript; Documentation; Cancer","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01005142,0.000243327,0.001210463,0.0002941799,0.0004773426,0.0001015052,0.0002954796,0.0002937659,0.00002554598],"category_scores_gemma":[0.00844985,0.0001767592,0.0003880323,0.0003442838,0.0001955184,0.0001390629,0.0002128084,0.0008682557,2.820611e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006442895,"about_ca_system_score_gemma":0.002736546,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04601905,"about_ca_topic_score_gemma":0.01650275,"domain_scores_codex":[0.9967177,0.000343587,0.0008991477,0.0008170355,0.0004255514,0.0007969743],"domain_scores_gemma":[0.9951297,0.0028434,0.0001892945,0.0007193547,0.0007501594,0.0003681139],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006938257,0.0002163887,0.607003,0.004222995,0.002128702,0.000005758591,0.0008153631,0.00002278756,0.002761825,0.0001138205,0.01313017,0.3626409],"study_design_scores_gemma":[0.01930766,0.0003935372,0.9090001,0.002254088,0.0008258063,0.000002228941,0.001760211,0.003540036,0.001228516,0.0001537308,0.06102409,0.0005100063],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.974726,0.01009356,0.001256574,0.003953981,0.00243882,0.005703331,0.001712615,0.00004807632,0.00006706183],"genre_scores_gemma":[0.9908841,0.002984719,0.001878724,0.0006748681,0.001393075,0.001067486,0.0003590684,0.00007680649,0.0006812157],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3621309,"threshold_uncertainty_score":0.9999024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3622858765974937,"score_gpt":0.6044427043004006,"score_spread":0.2421568277029069,"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."}}