{"id":"W4388520787","doi":"10.2967/jnumed.123.266388","title":"<sup>212</sup>Pb-Pretargeted Theranostics for Pancreatic Cancer","year":2023,"lang":"en","type":"article","venue":"Journal of Nuclear Medicine","topic":"Radiopharmaceutical Chemistry and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health; University of Alberta; National Cancer Institute; Australian Nuclear Science and Technology Organisation; U.S. Department of Energy","keywords":"Pretargeting; Medicine; Radioimmunotherapy; Pancreatic cancer; Nuclear medicine; In vivo; Cancer; Oncology; Internal medicine; Antibody; Immunology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003599094,0.0001287741,0.0004495141,0.00009568036,0.00008574231,0.000006624115,0.0001376424,0.00008471805,0.0009283095],"category_scores_gemma":[0.0006251619,0.00008739784,0.0001362157,0.0003586916,0.0001338784,0.00004380976,0.00001375892,0.0003182441,0.00003593578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006404093,"about_ca_system_score_gemma":0.00006768072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003679325,"about_ca_topic_score_gemma":8.809692e-8,"domain_scores_codex":[0.998811,0.00001739739,0.0004799917,0.0001216979,0.0003377868,0.0002321222],"domain_scores_gemma":[0.9988577,0.000248372,0.0001878014,0.0001763814,0.000269628,0.0002601256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001347334,0.0002350485,0.001186395,0.0007888249,0.0007702662,0.0002331547,0.001721763,0.000611462,0.4955229,0.0004988322,0.4829985,0.01408544],"study_design_scores_gemma":[0.009417028,0.001293004,0.005346681,0.001328189,0.00202937,0.0006538536,0.001559123,0.04277858,0.006826372,0.0009860215,0.927535,0.0002467922],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.903007,0.001961656,0.0004231357,0.09109918,0.0002686401,0.0005149523,0.00002623116,0.000104222,0.002594936],"genre_scores_gemma":[0.988104,0.002108754,0.001265826,0.00433495,0.002715366,0.00001452475,0.00001744613,0.00005582122,0.001383245],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4886966,"threshold_uncertainty_score":0.999985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05645402786274829,"score_gpt":0.3737715340278389,"score_spread":0.3173175061650906,"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."}}