{"id":"W4403734478","doi":"10.1007/s12043-024-02819-x","title":"Development of an intelligent linear regression model for dose estimation to patients during whole-body PET scan","year":2024,"lang":"en","type":"article","venue":"Pramana","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Heritage College","funders":"","keywords":"Linear regression; Regression; Computed tomography; Statistics; Estimation; Computer science; Nuclear medicine; Medicine; Radiology; Mathematics","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":[0.0001476116,0.00007913992,0.0001145218,0.00009903965,0.00005394881,0.00001270698,0.00006970677,0.00002619222,0.00001023716],"category_scores_gemma":[0.00007810926,0.00006143846,0.00003063122,0.0001150259,0.00001534905,0.00005685992,0.00004698394,0.00007648131,0.00001261369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007118631,"about_ca_system_score_gemma":0.00007937913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006822027,"about_ca_topic_score_gemma":0.00000259588,"domain_scores_codex":[0.9992411,0.000005169893,0.0002572462,0.0001949264,0.0001872255,0.0001144073],"domain_scores_gemma":[0.9995375,0.00001469963,0.00003679935,0.0001885078,0.00008052332,0.0001419266],"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":[0.0003613289,0.001632241,0.0004725892,0.003203433,0.00009857061,0.00001336601,0.006368207,0.001897769,0.1032952,0.00357493,0.009055732,0.8700266],"study_design_scores_gemma":[0.000210527,0.00007027763,0.0007973303,0.0007038395,0.00003097386,0.000002317961,0.0000184827,0.9493897,0.04327868,0.0003376226,0.005086345,0.00007393843],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6631319,0.00001413822,0.3348874,0.00115669,0.00002597686,0.0006128803,0.00001057521,0.000112911,0.00004750992],"genre_scores_gemma":[0.5747582,0.000004123116,0.4246101,0.00006482145,0.00002411198,0.0001404612,0.0001451287,0.00001284535,0.0002402191],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9474919,"threshold_uncertainty_score":0.2505388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04417423973968307,"score_gpt":0.3818858315699126,"score_spread":0.3377115918302296,"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."}}