{"id":"W4313420518","doi":"10.1016/j.chroma.2022.463717","title":"Determination of distribution coefficients of mercury and gold on selected extraction chromatographic resins - towards an improved separation method of mercury-197 from proton-irradiated gold targets","year":2022,"lang":"en","type":"article","venue":"Journal of Chromatography A","topic":"Radiopharmaceutical Chemistry and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia; University of Victoria; Simon Fraser University; TRIUMF","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canadian Cancer Society","keywords":"Chemistry; Mercury (programming language); Chromatography; Inductively coupled plasma mass spectrometry; Irradiation; Mass spectrometry; Analytical Chemistry (journal); Radiochemistry","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":[0.0005813479,0.0001983317,0.0006124791,0.0004035347,0.00008979516,0.00001107054,0.000150362,0.0001363152,0.00004947364],"category_scores_gemma":[0.0001216189,0.0001873019,0.0002481362,0.001509889,0.0001542296,0.0002171239,0.00002338118,0.0004297062,9.872712e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007695144,"about_ca_system_score_gemma":0.000179529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006509509,"about_ca_topic_score_gemma":0.00000171575,"domain_scores_codex":[0.9976062,0.0002635921,0.00106444,0.0002505994,0.0006393145,0.0001758139],"domain_scores_gemma":[0.9973611,0.0001375005,0.001473497,0.0002525159,0.0005906668,0.0001847147],"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":[0.00129434,0.001669462,0.003788173,0.0003307549,0.0002278551,0.000006921067,0.0003012102,0.00008512198,0.9879021,0.00006131871,0.0001056348,0.004227095],"study_design_scores_gemma":[0.003055668,0.002370441,0.1313191,0.0002145091,0.0006788856,0.000234787,0.0002246498,0.01581177,0.8450575,0.0002128949,0.0006357656,0.0001839583],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896413,0.0005285853,0.008319196,0.0001449376,0.00007247434,0.0007839267,0.0004305189,0.00002291001,0.00005617199],"genre_scores_gemma":[0.9956997,0.0001599899,0.003635101,0.00002153878,0.00005292227,0.00006000433,0.0003473101,0.00001951585,0.000003891961],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1428446,"threshold_uncertainty_score":0.7637949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01749492668356224,"score_gpt":0.3459402761034087,"score_spread":0.3284453494198464,"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."}}