{"id":"W4409158860","doi":"10.1117/12.3048474","title":"Prospective study on the reproducibility of radiomic features in the setting of variable CT contrast timing: initial results","year":2025,"lang":"en","type":"article","venue":"","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Reproducibility; Contrast (vision); Computer science; Variable (mathematics); Medical physics; Nuclear medicine; Biomedical engineering; Artificial intelligence; Medicine; Mathematics; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.008809572,0.0004941612,0.0004513947,0.000690126,0.0005134357,0.0007667029,0.0005438949,0.0005251732,0.0007881494],"category_scores_gemma":[0.02681015,0.0004815682,0.0005241935,0.0006511646,0.0008513283,0.000495802,0.0006805297,0.0004206039,0.000442712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005742167,"about_ca_system_score_gemma":0.0003811206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001264934,"about_ca_topic_score_gemma":0.001096359,"domain_scores_codex":[0.9938368,0.002899468,0.0006037399,0.001288855,0.001079428,0.0002916517],"domain_scores_gemma":[0.9600816,0.02166618,0.006297341,0.007148024,0.003758803,0.001048168],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001955507,0.000182931,0.9903273,0.00001747566,0.0001162507,0.0001219686,0.0004552265,0.0003831387,0.002302892,0.00002551246,0.00005089649,0.004060892],"study_design_scores_gemma":[0.00005549299,0.003976939,0.9891387,0.000004982909,0.0001100066,0.0006927763,0.0002263983,0.001268342,0.004119357,0.00002717613,0.0003535221,0.00002631335],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989325,0.0001099857,0.0006060539,0.000004302064,0.000002802876,0.00002481224,0.0000689361,0.000009604654,0.0002409504],"genre_scores_gemma":[0.9995798,0.000009115795,0.0002205749,0.000004263143,0.000004391901,0.00001781795,0.0001237462,0.000006349671,0.00003382971],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9911904,"threshold_uncertainty_score":0.04658997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01809296430121717,"score_gpt":0.3383081987779792,"score_spread":0.3202152344767621,"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."}}