{"id":"W4304014611","doi":"10.1002/mp.16032","title":"Publicly available framework for simulating and experimentally validating clinical PET systems","year":2022,"lang":"en","type":"article","venue":"Medical Physics","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Siemens Healthineers; Compute Canada; Canada Foundation for Innovation; Canada Research Chairs; Western Canada Research Grid; Radboud Universiteit","keywords":"Imaging phantom; Monte Carlo method; Image quality; Image resolution; Positron emission tomography; Ground truth; Medical imaging; Pipeline (software); Nuclear medicine; Computer science; Physics; Image (mathematics); Optics; Computer vision; Artificial intelligence; Mathematics; Statistics; Medicine","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":[0.004126815,0.003253651,0.001792983,0.002260352,0.0007669218,0.002962552,0.006776908,0.004057784,0.05956775],"category_scores_gemma":[0.01144836,0.001885274,0.003510524,0.001517745,0.0007615243,0.002092344,0.003604572,0.002941235,0.03270836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001663085,"about_ca_system_score_gemma":0.003201196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0100963,"about_ca_topic_score_gemma":0.009456837,"domain_scores_codex":[0.9981674,0.0004270118,0.0002156442,0.0002315904,0.0007649714,0.0001933679],"domain_scores_gemma":[0.9961227,0.001672219,0.000258403,0.0007881297,0.0009703474,0.0001881334],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001617649,0.0005704798,0.004873097,0.00464804,0.0006901568,0.001553958,0.0003453688,0.2346731,0.01370204,0.05819232,0.5327617,0.1463721],"study_design_scores_gemma":[0.0008891743,0.0001644528,0.001426831,0.0006827986,0.0001835815,0.000863345,0.00006179573,0.4937996,0.01300855,0.04140266,0.4472905,0.0002267994],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00276999,0.001975304,0.6072077,0.0008723798,0.0003923724,0.000696227,0.05951726,0.310851,0.01571776],"genre_scores_gemma":[0.08142449,0.003934387,0.5886742,0.00180927,0.0002598696,0.004082878,0.2312268,0.07547481,0.01311339],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05956775,"threshold_uncertainty_score":0.199274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1020701746137118,"score_gpt":0.4249646773287901,"score_spread":0.3228945027150783,"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."}}