{"id":"W4416385253","doi":"10.1021/acs.oprd.5c00326","title":"Simplifying “SiFA”: A High-Yielding, Automated Protocol for the One-Step Radiosynthesis of the Neuroendocrine Tumor Imaging Agent [ <sup>18</sup> F]SiTATE <i>via</i> a Merging of “Silicon-Fluoride Acceptor” (SiFA) and “Nonanhydrous, Minimally Basic” (NAMB) Chemistries","year":2025,"lang":"en","type":"article","venue":"Organic Process Research & Development","topic":"Radiopharmaceutical Chemistry and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; McMaster University","funders":"Canadian Institutes of Health Research; Saskatchewan Health Research Foundation; Canada Research Chairs; Neuroendocrine Tumor Research Foundation; Canada Foundation for Innovation; Natural Sciences and Engineering Research Council of Canada; McMaster University; Education and Research Foundation for Nuclear Medicine and Molecular Imaging","keywords":"Radiosynthesis; Protocol (science); Neuroendocrine tumors; Molecular imaging","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006220879,0.001112629,0.0004555358,0.0004422061,0.0004331882,0.0003691367,0.0007377903,0.0004331793,0.004800796],"category_scores_gemma":[0.000547786,0.0004412891,0.0004179173,0.0003693369,0.000460364,0.0006121309,0.0004780723,0.001314388,0.004897484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003792018,"about_ca_system_score_gemma":0.001122116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000892193,"about_ca_topic_score_gemma":0.002121,"domain_scores_codex":[0.9996057,0.00005372663,0.00003508283,0.0001134656,0.0001281205,0.00006394109],"domain_scores_gemma":[0.9997386,0.00006015172,0.00004779997,0.00006555763,0.0000612134,0.00002655843],"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":[0.0001340302,0.00003367443,0.0001367911,0.0001770835,0.00001755591,0.0001152961,0.00007102492,0.0003111527,0.9754564,0.00093181,0.001051643,0.02156352],"study_design_scores_gemma":[0.00001895608,0.0002695924,0.0005694842,0.00001573445,0.00001563903,0.0005932438,0.0000268939,0.001151658,0.9680895,0.0003395574,0.02887799,0.00003171705],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2152733,0.003612554,0.7446335,0.00068413,0.0004842611,0.002011088,0.002255917,0.007162835,0.02388245],"genre_scores_gemma":[0.4601392,0.005081587,0.5087882,0.0006660152,0.0001299915,0.001815793,0.005203725,0.001386102,0.01678952],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004800796,"threshold_uncertainty_score":0.01606029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04471368039633308,"score_gpt":0.3838993482905736,"score_spread":0.3391856678942406,"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."}}