{"id":"W2159485471","doi":"10.1021/bm4001662","title":"Dual-Purpose Polymer Labels for Fluorescent and Mass Cytometric Affinity Bioassays","year":2013,"lang":"en","type":"article","venue":"Biomacromolecules","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Alexander von Humboldt-Stiftung","keywords":"Bioassay; Fluorescence; Chemistry; Polymer; Dual (grammatical number); Fluorescent labelling; Biophysics; Chromatography; Organic chemistry; Biology; Ecology","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":[0.00007467337,0.00018085,0.0001329878,0.00008931971,0.0001393274,0.00005609915,0.0001144429,0.000150445,0.000008353399],"category_scores_gemma":[0.00005672697,0.0001631657,0.00007442961,0.0002070987,0.0001363599,0.00000525231,0.0001110775,0.00004075385,0.00001110798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001069063,"about_ca_system_score_gemma":0.00002158754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002412753,"about_ca_topic_score_gemma":0.000003437137,"domain_scores_codex":[0.9990407,0.00002194093,0.0001782176,0.0003950248,0.00008199225,0.0002821712],"domain_scores_gemma":[0.9993398,0.00001948173,0.00007690958,0.0003342017,0.0001140805,0.0001155324],"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":[0.00001284898,0.00005314756,0.0001529056,0.00001429207,0.00002052556,0.000001175615,0.000004092678,1.192787e-7,0.9846642,0.0006341548,0.003783778,0.01065876],"study_design_scores_gemma":[0.0003276025,0.0001880281,0.0007247005,0.000008242895,0.00001546938,0.00002136695,0.00001619799,0.00005048027,0.9783719,0.001057355,0.01898453,0.0002341635],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9362969,0.002842613,0.05817308,0.0009597382,0.00007187903,0.00108361,0.0001894584,0.0001092578,0.0002734301],"genre_scores_gemma":[0.9518635,0.0003183237,0.04671038,0.0002940952,0.0001160046,0.0001911807,0.0001720596,0.00003441717,0.000300049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01556655,"threshold_uncertainty_score":0.6653705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01106945054529885,"score_gpt":0.2611055069698628,"score_spread":0.2500360564245639,"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."}}