{"id":"W4403096183","doi":"10.1016/j.ejmcr.2024.100223","title":"Truncated NPY-based NPY(Y1)R-specific radiopeptides: Improved in vivo PET tumor imaging by application of peptidase inhibitors","year":2024,"lang":"en","type":"article","venue":"European Journal of Medicinal Chemistry Reports","topic":"Radiopharmaceutical Chemistry and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Bundesministerium für Bildung und Forschung; Deutsche Forschungsgemeinschaft","keywords":"In vivo; Chemistry; Endocrinology; Internal medicine; Medicine; Biology; Biotechnology","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":[0.0002557027,0.0004424135,0.0004803075,0.0001383263,0.00006808565,0.000294297,0.0003650627,0.00041862,0.000370218],"category_scores_gemma":[0.000248921,0.0001823703,0.0001922985,0.0001405892,0.0002037574,0.0002695999,0.0002094898,0.0004003851,0.0001969778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003797889,"about_ca_system_score_gemma":0.0001818918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006374676,"about_ca_topic_score_gemma":0.0007588953,"domain_scores_codex":[0.9998621,0.0000319497,0.00001265687,0.0000300045,0.00002605809,0.00003719225],"domain_scores_gemma":[0.999898,0.00002218278,0.00004064941,0.000007847863,0.00001190784,0.00001941609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001250786,0.00002368183,0.00003637524,0.00004598362,0.00000690366,0.00005361279,0.0000136654,0.0003769788,0.9980748,0.00004847519,0.00001665029,0.001177741],"study_design_scores_gemma":[0.00002603976,0.0005628755,0.0003720394,0.00000409533,0.00001914685,0.0001940454,0.000007092629,0.001222368,0.9962757,0.00001273649,0.001297094,0.000006841658],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9888954,0.002978442,0.006913402,0.00006311425,0.0000158911,0.00009648273,0.0001750529,0.0000609726,0.000801111],"genre_scores_gemma":[0.9856188,0.002087644,0.01052248,0.00007532939,0.000009706494,0.00008265743,0.0003239628,0.00002786797,0.001251436],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006374676,"threshold_uncertainty_score":0.002755523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00841985026210994,"score_gpt":0.2644412918796794,"score_spread":0.2560214416175695,"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."}}