{"id":"W4410613439","doi":"10.2967/jnumed.124.269098","title":"Can<sup>177</sup>Lu-DOTATATE Kidney Absorbed Doses be Predicted from Pretherapy SSTR PET? Findings from Multicenter Data","year":2025,"lang":"en","type":"article","venue":"Journal of Nuclear Medicine","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"National Cancer Institute","keywords":"Nuclear medicine; Radiochemistry; Absorbed dose; Medicine; Chemistry; Dosimetry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.009635909,0.0005808261,0.001097083,0.0007545066,0.000296626,0.00157304,0.001334098,0.0007299296,0.0009317736],"category_scores_gemma":[0.0187543,0.0004821571,0.001755719,0.001910053,0.0006140323,0.0008000855,0.0006739268,0.0006398741,0.0002896752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001972117,"about_ca_system_score_gemma":0.00229835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06966501,"about_ca_topic_score_gemma":0.09065088,"domain_scores_codex":[0.9952485,0.002371319,0.0003211378,0.001339173,0.0004892271,0.0002306086],"domain_scores_gemma":[0.9822544,0.006480162,0.00554461,0.003921532,0.001510722,0.0002885398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001474252,0.00005680628,0.9644259,0.0001272175,0.001504984,0.00007909126,0.0001841763,0.01100486,0.001871068,0.000298583,0.002250678,0.01672245],"study_design_scores_gemma":[0.0001701583,0.000430035,0.9381367,0.0001014358,0.002011187,0.0004857012,0.0003522042,0.04260158,0.004487592,0.0006492759,0.0104978,0.00007636239],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9631958,0.003758465,0.01544636,0.0009462301,0.00004399791,0.00008478781,0.01416154,0.0002441962,0.002118702],"genre_scores_gemma":[0.9868199,0.0003985909,0.004622117,0.000314969,0.00002184824,0.00005605094,0.007505683,0.00009934674,0.0001614369],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06966501,"threshold_uncertainty_score":0.138519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03403251073427317,"score_gpt":0.3365690487880175,"score_spread":0.3025365380537444,"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."}}