{"id":"W2058753079","doi":"10.1118/1.4800806","title":"Resolution modeling in PET imaging: Theory, practice, benefits, and pitfalls","year":2013,"lang":"en","type":"review","venue":"Medical Physics","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":353,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health","keywords":"Computer science; Context (archaeology); Positron emission tomography; Image resolution; Point spread function; Observer (physics); Resolution (logic); Medical imaging; Medical physics; Artificial intelligence; Nuclear medicine; Medicine; Physics","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":[0.005462071,0.001196335,0.002312921,0.002996145,0.0004827996,0.00290252,0.00300123,0.003883082,0.001882818],"category_scores_gemma":[0.007014638,0.001022719,0.001049238,0.003581264,0.002596766,0.004112305,0.001454644,0.003919095,0.002276003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001409549,"about_ca_system_score_gemma":0.001884622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002130029,"about_ca_topic_score_gemma":0.001820143,"domain_scores_codex":[0.9981853,0.0006197267,0.0001964596,0.0002273418,0.0007079958,0.00006306201],"domain_scores_gemma":[0.9940599,0.004580446,0.0002502801,0.0002998954,0.0007329251,0.00007657186],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004286701,0.00007034739,0.0005483712,0.01016066,0.0001231027,0.000589116,0.0002377863,0.008864572,0.001628837,0.09738261,0.01214526,0.8682065],"study_design_scores_gemma":[0.00002129155,0.0001870089,0.001108939,0.009076213,0.000187767,0.005762696,0.0003026327,0.01223614,0.004388826,0.1313854,0.8351555,0.0001875508],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003741423,0.9708282,0.02280228,0.002669043,0.0003379203,0.00001629061,0.00002168428,0.00004964021,0.0029008],"genre_scores_gemma":[0.006561245,0.9720182,0.01869787,0.0008617218,0.0007198987,0.00003504104,0.00003725122,0.00002970314,0.00103906],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005462071,"threshold_uncertainty_score":0.0288865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07700151388050115,"score_gpt":0.3870551149579711,"score_spread":0.3100536010774699,"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."}}