{"id":"W4410297426","doi":"10.1109/isbi60581.2025.10981186","title":"Disentangled PET Lesion Segmentation","year":2025,"lang":"en","type":"article","venue":"","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Segmentation; Computer science; Lesion; Artificial intelligence; Image segmentation; Computer vision; Medicine; Pathology","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":[0.001339273,0.001739897,0.001146435,0.001000253,0.0003658121,0.001964066,0.001152973,0.001795894,0.003288114],"category_scores_gemma":[0.005750244,0.0008567856,0.001265523,0.0005486599,0.0005746594,0.001638208,0.001792103,0.001985174,0.001231338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008480707,"about_ca_system_score_gemma":0.001223444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004510218,"about_ca_topic_score_gemma":0.008124028,"domain_scores_codex":[0.9993044,0.0001296634,0.00004289838,0.0002551647,0.0002090721,0.00005876433],"domain_scores_gemma":[0.9987161,0.0005566606,0.0001552055,0.00029468,0.000195796,0.00008144288],"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":[0.001321207,0.0001765238,0.009918759,0.0005063879,0.000352644,0.001157791,0.000349991,0.345611,0.1054438,0.00972346,0.008383018,0.5170555],"study_design_scores_gemma":[0.0000380925,0.00009005954,0.0022221,0.00004127377,0.00005375219,0.0009009893,0.00003504186,0.9435515,0.03810539,0.009761097,0.005151208,0.00004941392],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07912532,0.00130355,0.9097634,0.0005228246,0.0001256636,0.0001467647,0.0009093854,0.005540546,0.002562564],"genre_scores_gemma":[0.6047561,0.000663839,0.3818963,0.0006054112,0.00007316222,0.0001407389,0.003457048,0.002205002,0.006202332],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004510218,"threshold_uncertainty_score":0.01099986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02442422293280435,"score_gpt":0.3763649143698906,"score_spread":0.3519406914370862,"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."}}