{"id":"W2974156609","doi":"10.1002/jlcr.3805","title":"“In‐loop” carbonylation—A simplified method for carbon‐11 labelling of drugs and radioligands","year":2019,"lang":"en","type":"article","venue":"Journal of Labelled Compounds and Radiopharmaceuticals","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Horizon 2020 Framework Programme; H2020 Marie Skłodowska-Curie Actions; Karolinska Institutet; European Commission","keywords":"Radioligand; Chemistry; Carbonylation; Yield (engineering); High-performance liquid chromatography; Triethylamine; Raclopride; Benzoic acid; Chromatography; Carbon monoxide; Nuclear chemistry; Dopamine receptor D2; Organic chemistry; Materials science; Receptor; Catalysis","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":[],"consensus_categories":[],"category_scores_codex":[0.001215233,0.0001431792,0.0007237671,0.0002025233,0.00003781527,0.00001566974,0.00008990951,0.00009913363,0.00001444753],"category_scores_gemma":[0.00007492626,0.0001094063,0.00009804647,0.0001980499,0.0001007453,0.00006054739,0.00003249698,0.0002894614,1.893762e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003295021,"about_ca_system_score_gemma":0.00008138876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001477968,"about_ca_topic_score_gemma":2.254953e-7,"domain_scores_codex":[0.9985856,0.00005776506,0.0007300703,0.0001767704,0.0002399941,0.0002097451],"domain_scores_gemma":[0.998471,0.0006411956,0.0002903507,0.0001472696,0.0001938492,0.0002563583],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001109216,0.001218756,0.01748143,0.001329236,0.0004082579,0.00003786336,0.001061778,0.00002858177,0.9579554,0.01152392,0.001782776,0.006062832],"study_design_scores_gemma":[0.08637402,0.002406621,0.002435791,0.002118779,0.002375145,0.00249783,0.0007264562,0.4960915,0.2652785,0.01699396,0.1216889,0.001012525],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9851871,0.002891834,0.002903215,0.007839012,0.0001270865,0.0005830981,0.000005134334,0.00001290746,0.0004506554],"genre_scores_gemma":[0.9421118,0.001541254,0.05534366,0.0006037279,0.0001513575,0.000009722059,0.000001909296,0.00001977675,0.0002168013],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6926768,"threshold_uncertainty_score":0.4461461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0263989756144597,"score_gpt":0.3775361650076408,"score_spread":0.3511371893931811,"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."}}