{"id":"W4403129843","doi":"10.1007/978-3-031-73360-4_11","title":"Beyond Conventional Parametric Modeling: Data-Driven Framework for Estimation and Prediction of Time Activity Curves in Dynamic PET Imaging","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia, Okanagan Campus; Okanagan College","funders":"","keywords":"Computer science; Parametric statistics; Parametric model; Estimation; Estimation theory; Artificial intelligence; Data mining; Algorithm; Statistics; Mathematics","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":[0.001678515,0.0008820447,0.00146661,0.0004803391,0.0002494039,0.002042752,0.002059363,0.001862922,0.001687363],"category_scores_gemma":[0.004220759,0.001056036,0.00129425,0.001237148,0.0007780174,0.001877905,0.001063173,0.002482916,0.0008131317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006838112,"about_ca_system_score_gemma":0.001087282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005028502,"about_ca_topic_score_gemma":0.004669551,"domain_scores_codex":[0.9995958,0.0001405997,0.00002413185,0.0001176108,0.00008695941,0.00003485205],"domain_scores_gemma":[0.9983801,0.001201877,0.0001077556,0.0001440813,0.0001209377,0.00004534354],"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":[0.00009588714,0.00007190743,0.0007460527,0.0002396092,0.0001158236,0.000149696,0.00009623903,0.8060106,0.005068784,0.04266755,0.002804929,0.1419328],"study_design_scores_gemma":[0.000001739596,0.00001107324,0.0001011408,0.000008492763,0.000008539364,0.00003378347,0.000003365755,0.9854265,0.0004022988,0.01299917,0.0009960801,0.000007872715],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002374646,0.0008979943,0.995822,0.0001829622,0.00002685317,0.000009813703,0.0001024767,0.0002125889,0.0003707747],"genre_scores_gemma":[0.371303,0.005869322,0.6088123,0.0004789894,0.0003752048,0.0002202199,0.001216548,0.0006068256,0.01111763],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005028502,"threshold_uncertainty_score":0.0099985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0327280960039105,"score_gpt":0.335228529184614,"score_spread":0.3025004331807035,"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."}}