{"id":"W2026595385","doi":"10.1016/j.media.2007.12.002","title":"Multimodal image registration using floating regressors in the joint intensity scatter plot","year":2008,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Biomedical Imaging and Bioengineering; Natural Sciences and Engineering Research Council of Canada","keywords":"Image registration; Computer science; Artificial intelligence; Histogram; Robustness (evolution); Curse of dimensionality; Computer vision; Pattern recognition (psychology); Image (mathematics)","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":[0.002357122,0.0001977945,0.0004267126,0.0004602578,0.0002534084,0.0001781653,0.001118316,0.0001190172,0.0002774897],"category_scores_gemma":[0.002234257,0.0001400818,0.0002513813,0.002218944,0.0005613681,0.0009038037,0.0002654385,0.0005501527,0.00003456409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001015236,"about_ca_system_score_gemma":0.0001222485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001328281,"about_ca_topic_score_gemma":0.00009292644,"domain_scores_codex":[0.9961294,0.0004973086,0.0007504596,0.0005527383,0.001691255,0.000378858],"domain_scores_gemma":[0.9982291,0.0002203601,0.0002647408,0.0008399416,0.0002348562,0.0002109858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001449576,0.004926209,0.09074339,0.0003960869,0.003021732,0.02966225,0.07600166,0.0006210015,0.3707871,0.001053626,0.0785287,0.3441133],"study_design_scores_gemma":[0.0005091833,0.0000430344,0.02000937,0.00007095972,0.0001831116,0.0001872057,0.0004124971,0.9423944,0.03559876,0.000235346,0.00003238541,0.0003237494],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09346531,0.00002508086,0.9008818,0.004967606,0.0000521757,0.0001593913,0.000001128012,0.000149552,0.0002980109],"genre_scores_gemma":[0.6033285,0.00002874295,0.3919562,0.004498438,0.00009560678,0.00001367482,0.00001835534,0.00001002665,0.00005038209],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9417734,"threshold_uncertainty_score":0.571237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04663912200230379,"score_gpt":0.319221277277396,"score_spread":0.2725821552750922,"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."}}