{"id":"W4403013280","doi":"10.1101/2024.09.30.614929","title":"A novel method for harmonization of PET image spatial resolution without phantoms","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Harmonization; Image resolution; Resolution (logic); Computer vision; Medical physics; Computer science; Artificial intelligence; Nuclear medicine; Medicine; Physics; Acoustics","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":[0.002837173,0.0008429399,0.0007308571,0.001260233,0.000396034,0.001480493,0.001790319,0.001230236,0.003748943],"category_scores_gemma":[0.009515481,0.0006319962,0.00130747,0.001261141,0.0007399283,0.001432891,0.001786549,0.001061937,0.00144201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006434464,"about_ca_system_score_gemma":0.0008996779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001152467,"about_ca_topic_score_gemma":0.001075769,"domain_scores_codex":[0.9982888,0.0004996215,0.0001119348,0.0004110835,0.0005912918,0.00009716033],"domain_scores_gemma":[0.9970004,0.001316135,0.0002993622,0.0007301472,0.000580326,0.0000735545],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004256724,0.0001807563,0.001949234,0.0003181014,0.0002172006,0.0002549911,0.0003485437,0.1380162,0.1000405,0.02941073,0.003789543,0.7250486],"study_design_scores_gemma":[0.00003464655,0.0001111479,0.001195286,0.00002179848,0.00005294176,0.0004209394,0.00003471614,0.9512312,0.02977812,0.00849767,0.008575724,0.00004574134],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001559964,0.00003408283,0.9978021,0.00001870232,0.0000121402,0.00002017797,0.00001687747,0.0002774523,0.0002585311],"genre_scores_gemma":[0.05612019,0.00009045435,0.9415827,0.00007668017,0.00004360983,0.0001235496,0.0001668386,0.0004112259,0.00138488],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003748943,"threshold_uncertainty_score":0.01500458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02515151492214533,"score_gpt":0.3135431232676266,"score_spread":0.2883916083454813,"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."}}