{"id":"W7160022158","doi":"10.1109/iccv51701.2025.01851","title":"MRGen: Segmentation Data Engine for Underrepresented MRI Modalities","year":2025,"lang":"","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Key Research and Development Program of China","keywords":"Segmentation; Modalities; Pattern recognition (psychology); Modality (human–computer interaction); Image segmentation","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":[],"consensus_categories":[],"category_scores_codex":[0.001407265,0.002414967,0.0014063,0.003586038,0.0006745688,0.002649736,0.002702984,0.001853396,0.02973899],"category_scores_gemma":[0.006147754,0.001481524,0.001583354,0.002451298,0.0006428521,0.002375128,0.002950465,0.001667882,0.01781178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00102012,"about_ca_system_score_gemma":0.001837869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003890685,"about_ca_topic_score_gemma":0.007670472,"domain_scores_codex":[0.9993512,0.0000631067,0.00009494974,0.0002067091,0.0002173643,0.0000666316],"domain_scores_gemma":[0.9981403,0.0006117015,0.0001257687,0.0006660166,0.0003415073,0.0001146956],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002990783,0.0002180995,0.006849692,0.001918507,0.0005514161,0.001013491,0.0007280703,0.01582562,0.04082649,0.02242921,0.514496,0.3921526],"study_design_scores_gemma":[0.0008538648,0.0002744345,0.006201206,0.0004383895,0.0003737422,0.001993961,0.000315365,0.1625932,0.155667,0.05228302,0.6186858,0.0003199559],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.008638358,0.0008714174,0.4121176,0.0005184977,0.0002098418,0.0003273152,0.06922855,0.503258,0.004830403],"genre_scores_gemma":[0.1134972,0.001521251,0.5256931,0.001298523,0.000216006,0.001235843,0.2455208,0.09991483,0.01110252],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02973899,"threshold_uncertainty_score":0.09948683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07522969786579645,"score_gpt":0.3926160744130011,"score_spread":0.3173863765472046,"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."}}