{"id":"W4415077465","doi":"10.1007/978-3-032-07502-4_10","title":"Imagining Alternatives: Towards High-Resolution 3D Counterfactual Medical Image Generation via Language Guidance","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Counterfactual thinking; Medical imaging; Fidelity; Image (mathematics); Natural language; Natural language generation; Limiting; Visualization","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001399566,0.0006382633,0.0006331063,0.0006365422,0.0003716077,0.0008027024,0.003161073,0.0003476581,0.0001248872],"category_scores_gemma":[0.0003722773,0.00058207,0.0001431486,0.0005340017,0.0008052797,0.001219022,0.001553601,0.000884224,0.00004209579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004790349,"about_ca_system_score_gemma":0.001031322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002709664,"about_ca_topic_score_gemma":0.0002218276,"domain_scores_codex":[0.9949797,0.0001319893,0.0007016051,0.001769976,0.001691256,0.0007255004],"domain_scores_gemma":[0.9974853,0.0003488448,0.0003514488,0.001162463,0.0004407218,0.0002112668],"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":[0.000008046147,0.0000347987,0.000006111001,0.00002974324,0.00003454748,0.0001740873,0.00135668,0.05096389,0.002059305,0.003615608,0.0004034981,0.9413137],"study_design_scores_gemma":[0.0003185531,0.00009514576,0.00003750384,0.0003943237,0.00001283005,0.00003059796,5.204571e-7,0.9837058,0.009228781,0.004771214,0.0008323458,0.0005723782],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00006024211,0.0009991807,0.989562,0.001788026,0.003540032,0.0003240839,0.00001660204,0.0001593486,0.003550481],"genre_scores_gemma":[0.2429851,0.0001248187,0.7508839,0.002723719,0.002537912,0.00001848727,0.00003225077,0.00003827114,0.0006554858],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9407413,"threshold_uncertainty_score":0.9996631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01162071691506672,"score_gpt":0.2573483645142772,"score_spread":0.2457276475992105,"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."}}