{"id":"W2134375305","doi":"10.1118/1.1414309","title":"Automated seed detection and three‐dimensional reconstruction. II. Reconstruction of permanent prostate implants using simulated annealing","year":2001,"lang":"en","type":"article","venue":"Medical Physics","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Hôtel-Dieu de Québec; Centre hospitalier de l'Université Laval; Centre hospitalier universitaire de Québec","funders":"","keywords":"Simulated annealing; Matching (statistics); Iterative reconstruction; Computer science; Algorithm; Artificial intelligence; Calibration; 3D reconstruction; Radiography; Computer vision; Mathematics; Medicine; Radiology; Statistics","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":[0.0001359811,0.0001553642,0.0003210417,0.00006029631,0.0001630701,0.000008145597,0.00002537544,0.0001151717,0.00004960122],"category_scores_gemma":[0.00004530328,0.0001293637,0.00005984759,0.000218959,0.0001714082,0.0001146778,0.00003756309,0.0001706517,0.000002426328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001416719,"about_ca_system_score_gemma":0.0001371083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002210106,"about_ca_topic_score_gemma":0.00002310588,"domain_scores_codex":[0.9987738,0.00002564055,0.0003568732,0.0002632854,0.0003668951,0.0002135354],"domain_scores_gemma":[0.9993071,0.00004800829,0.0001597769,0.0001268231,0.0001544428,0.0002038727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007985781,0.0004853329,0.3188436,0.0002305647,0.0004262807,0.000157585,0.000306685,0.00231063,0.01971427,0.00001362085,0.00003079575,0.656682],"study_design_scores_gemma":[0.007701956,0.001097837,0.1223818,0.001801416,0.0004799039,0.005199432,0.00008393695,0.7792,0.08017765,0.001404503,0.00009604602,0.0003755832],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998356,0.0002558316,0.0002787899,0.0001659861,0.0003723304,0.0003617294,0.00001959253,0.0001411119,0.000048563],"genre_scores_gemma":[0.9992023,0.0001725834,0.00029292,0.000101873,0.0001658381,0.000005035381,0.00003399161,0.0000180872,0.000007406039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7768894,"threshold_uncertainty_score":0.5275298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0208122439588303,"score_gpt":0.2812063897385602,"score_spread":0.2603941457797299,"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."}}