{"id":"W2784122696","doi":"10.1021/acs.jmedchem.7b01754","title":"Development of Candidates for Positron Emission Tomography (PET) Imaging of Ghrelin Receptor in Disease: Design, Synthesis, and Evaluation of Fluorine-Bearing Quinazolinone Derivatives","year":2018,"lang":"en","type":"article","venue":"Journal of Medicinal Chemistry","topic":"Adipose Tissue and Metabolism","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cancer Care Ontario; Lawson Health Research Institute","funders":"Institute of Cancer Research; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Prostate Cancer Canada","keywords":"Chemistry; Positron emission tomography; Quinazolinone; Ghrelin; Pet imaging; Bearing (navigation); Fluorine; Chemical synthesis; Receptor; Combinatorial chemistry; Biochemistry; Nuclear medicine; Organic chemistry; In vitro; Artificial intelligence","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":[0.0004942795,0.0004704233,0.0004054178,0.0002485543,0.0001611169,0.0002850577,0.0005931391,0.000331946,0.001965214],"category_scores_gemma":[0.0002754687,0.0002307167,0.0002356839,0.0002021246,0.000305277,0.0003384031,0.0001793295,0.0004653395,0.0005880082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000513007,"about_ca_system_score_gemma":0.0003924832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000783941,"about_ca_topic_score_gemma":0.001436838,"domain_scores_codex":[0.9998817,0.00003472094,0.00000649007,0.0000212965,0.00002262308,0.00003313955],"domain_scores_gemma":[0.9998777,0.00002378911,0.00002872362,0.000008989214,0.00002631181,0.00003440122],"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":[0.0005439594,0.0003306221,0.0006565979,0.0004175525,0.00002864381,0.0004440967,0.0001446927,0.003512443,0.9688803,0.00190797,0.0005410941,0.0225921],"study_design_scores_gemma":[0.001292832,0.01543343,0.005257366,0.000107448,0.000129271,0.001318036,0.0001141934,0.007785571,0.9332753,0.0005213926,0.03466528,0.00009992815],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.91936,0.02240084,0.04818931,0.001055567,0.0001145385,0.001435825,0.0009211067,0.0003635745,0.006159298],"genre_scores_gemma":[0.9637578,0.008389605,0.02240166,0.0002447767,0.00002748396,0.0004073318,0.0006972966,0.00003381762,0.004040164],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001965214,"threshold_uncertainty_score":0.006574333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02708392207481365,"score_gpt":0.318455797496598,"score_spread":0.2913718754217844,"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."}}