{"id":"W4409866408","doi":"10.3389/fdest.2025.1488822","title":"Design of a high-resolution liquid xenon detector for positron emission tomography","year":2025,"lang":"en","type":"article","venue":"Frontiers in Detector Science and Technology","topic":"Atomic and Subatomic Physics Research","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bishop's University","funders":"","keywords":"Xenon; Positron emission tomography; Detector; Resolution (logic); Positron emission; Tomography; Physics; Materials science; Brain positron emission tomography; Nuclear physics; Nuclear medicine; Optics; Preclinical imaging; Computer science; Medicine; In vivo; Artificial intelligence","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":[0.0004824393,0.0001234141,0.0002637754,0.001181159,0.00019186,0.00002041537,0.0004480184,0.0001010137,0.00000342563],"category_scores_gemma":[0.00005543325,0.0001143152,0.00003668874,0.002108766,0.0007972316,0.0001460402,0.0001537983,0.0001710485,3.432678e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001062319,"about_ca_system_score_gemma":0.0004300339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006527339,"about_ca_topic_score_gemma":0.000001090675,"domain_scores_codex":[0.9987906,0.0000263703,0.0002179364,0.0003838331,0.000173608,0.0004076205],"domain_scores_gemma":[0.9993849,0.00005393329,0.00007634549,0.0002588606,0.0001778831,0.00004801759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005469068,0.0001340167,0.02915326,0.00005230902,0.00005642859,7.92832e-7,0.0001381678,0.0000593706,0.6448779,0.01734359,0.000925887,0.3067114],"study_design_scores_gemma":[0.001017169,0.0002748209,0.0004749148,0.00007069232,0.00001778462,3.732479e-7,0.0004586786,0.06940753,0.8388928,0.08894596,0.0002641834,0.0001751643],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4991339,0.0002301566,0.4998826,0.0001288471,0.0001578707,0.0003536652,0.000007103867,0.00002466087,0.00008112633],"genre_scores_gemma":[0.9897238,0.00001107307,0.01008241,0.000008490372,0.0000161937,0.0001031942,0.000001514923,0.000006671691,0.00004663177],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4905899,"threshold_uncertainty_score":0.4661638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007256485943018118,"score_gpt":0.254009791737429,"score_spread":0.2467533057944109,"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."}}