{"id":"W2146330379","doi":"10.1109/iembs.2005.1616449","title":"Intensity Robust Viscous Fluid Deformation Based Morphometry Using Regionally Adapted Mutual Information","year":2005,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Deformation (meteorology); Mutual information; Intensity (physics); Geology; Computer science; Artificial intelligence; Physics; Optics","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":[],"consensus_categories":[],"category_scores_codex":[0.0004367401,0.0001293057,0.0001332321,0.0003619043,0.0001189772,0.0001938863,0.0004343518,0.00008027402,0.0001480223],"category_scores_gemma":[0.0001571733,0.0001157467,0.00005088377,0.0005480917,0.00005000409,0.004882254,0.0001313425,0.0001310939,0.0001580215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002095857,"about_ca_system_score_gemma":0.0001272266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005263243,"about_ca_topic_score_gemma":0.000005757778,"domain_scores_codex":[0.9985518,0.0000451976,0.0004470418,0.0001580891,0.0005901137,0.0002077526],"domain_scores_gemma":[0.9989378,0.00004814317,0.0001731844,0.0003519793,0.0003647039,0.0001241644],"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":[0.0001535621,0.0004656035,0.0005343701,0.0001468251,0.00007284602,0.00002106893,0.00282733,0.05311047,0.04381015,0.0148727,0.09114882,0.7928362],"study_design_scores_gemma":[0.0003137033,0.00004153517,0.0004287717,0.00002119068,0.000004112304,0.00003098763,0.0000596107,0.9443985,0.05380534,0.00007713849,0.0006708964,0.0001482155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008672401,0.000006439425,0.9877024,0.001125978,0.0001099271,0.0002079362,0.000001650939,0.0006216841,0.001551564],"genre_scores_gemma":[0.2839003,0.000002572412,0.7097016,0.006272165,0.00004251411,0.00000608041,0.00003680184,0.00000406345,0.00003394538],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.891288,"threshold_uncertainty_score":0.4720012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03072580737994779,"score_gpt":0.2588863381075773,"score_spread":0.2281605307276295,"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."}}