{"id":"W4409567218","doi":"10.3390/a18040233","title":"Patient-Specific Hyperparameter Optimization of a Deep Learning-Based Tumor Autocontouring Algorithm on 2D Liver, Prostate, and Lung Cine MR Images: A Pilot Study","year":2025,"lang":"en","type":"article","venue":"Algorithms","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Alberta","funders":"Canadian Institutes of Health Research","keywords":"Hyperparameter; Prostate; Lung; Algorithm; Artificial intelligence; Computer science; Medicine; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0001221699,0.0002560108,0.000352232,0.0002070084,0.0001412351,0.00005104554,0.0001116295,0.00002164656,0.00007721647],"category_scores_gemma":[0.000008631244,0.0002403034,0.00005230655,0.0002776224,0.00008088912,0.0001597238,0.00004940106,0.0002377698,6.991511e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006100588,"about_ca_system_score_gemma":0.00002800275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001167516,"about_ca_topic_score_gemma":7.207479e-7,"domain_scores_codex":[0.9986892,0.000105224,0.0003532446,0.0004239062,0.0001787566,0.000249664],"domain_scores_gemma":[0.9992129,0.0001329516,0.0002044344,0.0002699428,0.000127075,0.00005266919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003208285,0.003072676,0.01819091,0.00006773003,0.0003418621,0.00003664007,0.001127613,0.1070698,0.001373778,0.0001062672,0.0001409548,0.8681509],"study_design_scores_gemma":[0.003519154,0.004995586,0.001943087,0.0001864347,0.00007262608,0.00000164431,0.0005957599,0.9749911,0.01259938,0.0001080174,0.0005600284,0.000427173],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03199065,0.0006045011,0.9650756,0.0000208888,0.00007923547,0.001757837,0.00002414734,0.0001501019,0.0002970436],"genre_scores_gemma":[0.6944696,0.00003250643,0.3047003,0.00005727438,0.0000746778,0.0004209756,0.00003214476,0.00005121467,0.0001612901],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8679214,"threshold_uncertainty_score":0.9799287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007089357906349622,"score_gpt":0.2507818295171732,"score_spread":0.2436924716108236,"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."}}