{"id":"W2963591880","doi":"10.1016/j.eurpolymj.2019.08.002","title":"A metal-chelating polymer for chelating zirconium and its use in mass cytometry","year":2019,"lang":"en","type":"article","venue":"European Polymer Journal","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Fluidigm (Canada); University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chelation; Polymer; Zirconium; Metal ions in aqueous solution; Chemistry; Polystyrene; Nuclear chemistry; Metal; Mass cytometry; PEG ratio; Polyethylene glycol; Materials science; Polymer chemistry; Inorganic chemistry; Organic chemistry; Biochemistry","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":[0.0006254381,0.0001995135,0.0002180272,0.0001731352,0.0001156002,0.0001051845,0.0001282741,0.0000838184,0.000006715194],"category_scores_gemma":[0.0001470075,0.0001720471,0.0001440361,0.000152183,0.0000345354,0.00002766735,0.00009467722,0.0002604644,0.000006187146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001484557,"about_ca_system_score_gemma":0.00002458905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003614766,"about_ca_topic_score_gemma":0.000002594119,"domain_scores_codex":[0.9986439,0.0001755554,0.0003793466,0.000340411,0.0001255745,0.0003352214],"domain_scores_gemma":[0.9993579,0.00003629365,0.0002358509,0.000187675,0.00007532017,0.0001069502],"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":[0.00005237299,0.00001772916,0.007222704,0.000009624226,0.00007024344,0.00001415361,0.00002971617,0.000002766112,0.9896801,0.00003687602,0.00004745068,0.002816274],"study_design_scores_gemma":[0.0007339208,0.0001849181,0.002319432,0.00006321871,0.00004157598,0.0001941237,0.00008379397,0.0002255617,0.9945061,0.00001132289,0.001363871,0.0002721818],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924418,0.003472464,0.002510099,0.000109418,0.0001030992,0.0001277385,0.0000127298,0.00002080361,0.001201859],"genre_scores_gemma":[0.9921452,0.0001251219,0.003403976,0.0003323305,0.0003080018,0.00000123858,0.00001678765,0.00005118074,0.003616181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004903272,"threshold_uncertainty_score":0.7015879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01543989490324855,"score_gpt":0.2633331972537604,"score_spread":0.2478933023505118,"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."}}