{"id":"W4389999783","doi":"10.1002/mrc.5421","title":"A reliable external calibration method for reaction monitoring with benchtop NMR","year":2023,"lang":"en","type":"article","venue":"Magnetic Resonance in Chemistry","topic":"Analytical Chemistry and Chromatography","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Structural Genomics Consortium; University of Toronto; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Genentech; University of British Columbia; Canada Foundation for Innovation","keywords":"Chemistry; Analyte; Nuclear magnetic resonance spectroscopy; Calibration; Proton NMR; Analytical Chemistry (journal); Relaxometry; Spectrometer; Biological system; Process engineering; Nuclear magnetic resonance; Chromatography; Magnetic resonance imaging; Spin echo; Organic chemistry","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":[0.000185298,0.0002317294,0.0002433658,0.00003368422,0.0000917945,0.00005529524,0.000231386,0.0002344907,0.0003239991],"category_scores_gemma":[0.00008626721,0.0002272672,0.00009713865,0.0005088426,0.00006681314,0.0001115651,0.0000420151,0.0002942663,0.000006160278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007918084,"about_ca_system_score_gemma":0.00005759368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006519499,"about_ca_topic_score_gemma":0.000002619337,"domain_scores_codex":[0.9983539,0.000006048973,0.0003473758,0.0005271431,0.0003117829,0.000453761],"domain_scores_gemma":[0.9991772,0.000172846,0.00009637781,0.0003845035,0.00005903871,0.0001100783],"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":[0.0001847295,0.00006577355,0.02542818,0.0007439507,0.000008327434,0.00004835518,0.00007268284,0.0001719075,0.9638337,0.00002375233,0.0004589237,0.008959653],"study_design_scores_gemma":[0.001043721,0.00002998748,0.002646439,0.0005353433,0.00003249009,0.00003571129,0.0003435775,0.02043958,0.9637954,0.001279827,0.009459862,0.0003581173],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9838685,0.001245605,0.001345259,0.0002280396,0.0000429475,0.0001230738,0.00003010982,0.0002783297,0.01283817],"genre_scores_gemma":[0.9619145,0.0003314592,0.0160025,0.00002600466,0.0007542642,0.0005494356,0.0001106433,0.00008089194,0.02023028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02278174,"threshold_uncertainty_score":0.9267688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01463190394303963,"score_gpt":0.2714253648261448,"score_spread":0.2567934608831051,"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."}}