{"id":"W4303962082","doi":"10.3390/pharmaceutics14102114","title":"Toward Optimized 89Zr-Immuno-PET: Side-by-Side Comparison of [89Zr]Zr-DFO-, [89Zr]Zr-3,4,3-(LI-1,2-HOPO)- and [89Zr]Zr-DFO*-Cetuximab for Tumor Imaging: Which Chelator Is the Most Suitable?","year":2022,"lang":"en","type":"article","venue":"Pharmaceutics","topic":"Radiopharmaceutical Chemistry and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Deutsche Forschungsgemeinschaft; Bundesministerium für Bildung und Forschung; Wilhelm Sander-Stiftung","keywords":"Cetuximab; Biodistribution; Chemistry; Pet imaging; Derivatization; Chelation; In vivo; Positron emission tomography; Ex vivo; Radiochemistry; Nuclear chemistry; Nuclear medicine; Chromatography; High-performance liquid chromatography; In vitro; Monoclonal antibody; Antibody; Biochemistry; Organic chemistry; Medicine","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001488937,0.0008920699,0.001522035,0.0001705289,0.001165091,0.000159767,0.001059704,0.0001573172,0.001172231],"category_scores_gemma":[0.0004413085,0.0008094307,0.0004340978,0.001246981,0.0006719488,0.0002945737,0.0006390195,0.002092537,0.0000391827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004234582,"about_ca_system_score_gemma":0.0005192183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005444175,"about_ca_topic_score_gemma":0.000002200508,"domain_scores_codex":[0.9943018,0.0002568682,0.001674263,0.001203767,0.001168344,0.001394949],"domain_scores_gemma":[0.9954935,0.001107965,0.0007363064,0.001260703,0.0006065197,0.0007949811],"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":[0.005957023,0.005177106,0.01268178,0.003136983,0.002178885,0.0001048853,0.005215042,0.001897962,0.8173255,0.001356822,0.1317818,0.0131862],"study_design_scores_gemma":[0.01268877,0.0002308823,0.0002007485,0.00009846543,0.00196653,0.0005301574,0.002561389,0.101002,0.4290848,0.0003328289,0.4503902,0.0009132847],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.839587,0.05079117,0.006086084,0.05842849,0.002115253,0.01418086,0.006878157,0.00111124,0.02082171],"genre_scores_gemma":[0.9866583,0.0009749632,0.002484876,0.005208327,0.0004556217,0.001471347,0.0005161271,0.0001999446,0.0020305],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3882407,"threshold_uncertainty_score":0.9997408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06496952678977488,"score_gpt":0.3815009955512827,"score_spread":0.3165314687615078,"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."}}