{"id":"W2328494350","doi":"10.1021/bc3002437","title":"Novel Radiolabeled Peptides for Breast and Prostate Tumor PET Imaging: <sup>64</sup>Cu/and <sup>68</sup>Ga/NOTA-PEG-[<scp>d</scp>-Tyr<sup>6</sup>,βAla<sup>11</sup>,Thi<sup>13</sup>,Nle<sup>14</sup>]BBN(6–14)","year":2012,"lang":"en","type":"article","venue":"Bioconjugate Chemistry","topic":"Radiopharmaceutical Chemistry and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency; Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"Canadian Institutes of Health Research","keywords":"Chemistry; Biodistribution; Bombesin; Imaging agent; In vivo; Peptide; Pharmacokinetics; Prostate cancer; PEG ratio; Prostate; Receptor; Cancer research; Cancer; In vitro; Biochemistry; Internal medicine; Medicine; Neuropeptide","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":[0.0002067475,0.0003862738,0.0002919078,0.0001057252,0.00009168955,0.0002362874,0.0002810181,0.0005116491,0.0005172838],"category_scores_gemma":[0.0001603934,0.0001687967,0.0001359023,0.0001614796,0.000154241,0.0002746136,0.000163206,0.0003690898,0.0002558703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003602049,"about_ca_system_score_gemma":0.0001730002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006877056,"about_ca_topic_score_gemma":0.0007563755,"domain_scores_codex":[0.9998857,0.00002981776,0.000005838304,0.00002948359,0.00003004076,0.00001916855],"domain_scores_gemma":[0.9999468,0.000009747854,0.00001504749,0.000003882609,0.00001379219,0.00001072976],"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":[0.0001328206,0.0000139883,0.0000880673,0.00008481918,0.000005230257,0.0000597898,0.00001248801,0.0002429321,0.9961478,0.00008223207,0.00005253175,0.003077475],"study_design_scores_gemma":[0.00002903768,0.0003895976,0.001345527,0.000008984403,0.00002131005,0.001088488,0.00001414023,0.001990326,0.9892923,0.00003368954,0.005774676,0.00001189593],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9294768,0.02013886,0.04587201,0.0003148716,0.0001037005,0.0001900676,0.0003854964,0.0001806905,0.003337451],"genre_scores_gemma":[0.9461177,0.005891002,0.04246307,0.0001687412,0.00003610938,0.0001720382,0.0005189312,0.0000495693,0.00458284],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006877056,"threshold_uncertainty_score":0.002613485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01755169313663164,"score_gpt":0.2694832360236755,"score_spread":0.2519315428870438,"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."}}