{"id":"W7084447505","doi":"","title":"ProbMed: A Probabilistic Framework for Medical Multimodal Binding","year":2025,"lang":"en","type":"article","venue":"ArXiv.org","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; University of Toronto","keywords":"Probabilistic logic; Modalities; Embedding; Modality (human–computer interaction); Medical diagnosis; Statistical model; Hellinger distance; Probabilistic relevance model","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.003681056,0.001253728,0.001075559,0.001969625,0.0006605142,0.001953763,0.003267715,0.002225083,0.005124835],"category_scores_gemma":[0.01197922,0.000980976,0.001860053,0.001453557,0.001584776,0.003226733,0.004299933,0.003403982,0.001727497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001807351,"about_ca_system_score_gemma":0.001807366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005023018,"about_ca_topic_score_gemma":0.006484481,"domain_scores_codex":[0.9979435,0.0008821264,0.00010242,0.0004772331,0.0004763314,0.0001184074],"domain_scores_gemma":[0.9969272,0.001911783,0.0002536587,0.0003650919,0.0003806805,0.0001617163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003905387,0.0002107247,0.00283409,0.0004118134,0.0002294578,0.0004203051,0.0003238286,0.5245257,0.004543873,0.1006004,0.01825891,0.3472504],"study_design_scores_gemma":[0.00001722252,0.00006070289,0.0002710529,0.00003618177,0.00001880079,0.0001972674,0.00002013095,0.9324726,0.001233152,0.06119245,0.004457578,0.00002285987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001627894,0.0003272969,0.995791,0.0003911764,0.00003213151,0.00004307539,0.0003215215,0.0008698152,0.0005959928],"genre_scores_gemma":[0.2942961,0.001459751,0.6899194,0.001405865,0.0004948776,0.0007027307,0.003292569,0.0008073738,0.007621311],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005124835,"threshold_uncertainty_score":0.01946747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02098385975019209,"score_gpt":0.2971736970367127,"score_spread":0.2761898372865206,"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."}}