{"id":"W3213166136","doi":"10.1007/s11307-021-01675-0","title":"Repurposing [11C]MC1 for PET Imaging of Cyclooxygenase-2 in Colorectal Cancer Xenograft Mouse Models","year":2021,"lang":"en","type":"article","venue":"Molecular Imaging and Biology","topic":"Inflammatory mediators and NSAID effects","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Institutes of Health; Centre for Addiction and Mental Health Foundation; Canada Excellence Research Chairs, Government of Canada; Azrieli Foundation; Canada Foundation for Innovation; Ontario Research Foundation; Foundation for the National Institutes of Health","keywords":"Colorectal cancer; Biodistribution; Positron emission tomography; Cyclooxygenase; Celecoxib; Medicine; Ex vivo; Cancer; In vivo; Cancer research; Nuclear medicine; Pathology; Chemistry; Internal medicine; Biology; Enzyme","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002411198,0.0001454485,0.0003588636,0.00012426,0.00004420467,0.00001048167,0.00004196234,0.00004385613,0.000006167335],"category_scores_gemma":[0.00009982629,0.0001310065,0.00008972229,0.0001247165,0.0001213915,0.00004188014,0.00005128137,0.0001291006,3.618686e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003781326,"about_ca_system_score_gemma":0.0001286912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001711996,"about_ca_topic_score_gemma":0.00003212323,"domain_scores_codex":[0.9989646,0.00008370247,0.0002533773,0.0003248423,0.00005860807,0.0003148661],"domain_scores_gemma":[0.9995297,0.00006156383,0.00007484446,0.0001359946,0.0001177006,0.00008018271],"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":[0.0001443073,0.00005299788,0.07368441,0.0001786533,0.00003733986,0.0003955248,0.0001923319,0.00006232813,0.9167041,0.0002688835,0.00008687066,0.008192248],"study_design_scores_gemma":[0.003012094,0.0001039544,0.003424686,0.0002454781,0.0001090352,0.0004582501,0.0002050349,0.06228728,0.9279849,0.0007454345,0.001165654,0.0002582235],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880138,0.008955985,0.001749074,0.0006622216,0.0001512473,0.0002860563,0.00002495655,0.00002806724,0.0001286052],"genre_scores_gemma":[0.9970851,0.000262547,0.001793973,0.0006392427,0.00006220197,0.0000605754,0.00005083255,0.00002438218,0.00002112524],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07025972,"threshold_uncertainty_score":0.5342289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01193333200017061,"score_gpt":0.2887832246447001,"score_spread":0.2768498926445295,"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."}}