{"id":"W2542972438","doi":"10.1109/nssmic.2011.6153730","title":"Assessment of bootstrap resampling accuracy for PET data","year":2011,"lang":"en","type":"article","venue":"","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Engineering and Physical Sciences Research Council; Canada Research Chairs","keywords":"Resampling; Metric (unit); Divergence (linguistics); Nonparametric statistics; Computer science; Data set; Voxel; Statistics; Mathematics; Similarity (geometry); Sampling distribution; Pattern recognition (psychology); Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05585554,0.0009265049,0.001144204,0.002449487,0.0009847361,0.001291277,0.001344636,0.002068779,0.001264892],"category_scores_gemma":[0.1732163,0.0003260386,0.001060056,0.00174053,0.00165187,0.001344179,0.001822814,0.001043991,0.0005542905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004921788,"about_ca_system_score_gemma":0.0006566272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001583248,"about_ca_topic_score_gemma":0.001453773,"domain_scores_codex":[0.9783718,0.01313013,0.002030887,0.001851871,0.004200887,0.000414381],"domain_scores_gemma":[0.8204788,0.1374163,0.00764059,0.01862646,0.01495073,0.0008870356],"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":[0.008569418,0.0006594724,0.1897829,0.002215273,0.002344864,0.001933979,0.003400196,0.3774483,0.03413212,0.01888646,0.007064695,0.3535623],"study_design_scores_gemma":[0.0001945077,0.001470765,0.08771514,0.0004392774,0.0003749889,0.001675068,0.0009528907,0.8458057,0.04349998,0.01030784,0.007364468,0.0001994075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4720529,0.003653491,0.5152278,0.0005310875,0.0002607462,0.0007621543,0.001479415,0.002335016,0.00369728],"genre_scores_gemma":[0.8385548,0.0005047129,0.1564827,0.0001693174,0.00007263012,0.0005455343,0.002503181,0.0005333393,0.0006338145],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05585554,"threshold_uncertainty_score":0.2953959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3902970409938821,"score_gpt":0.501862949996647,"score_spread":0.111565909002765,"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."}}