{"id":"W4389978759","doi":"10.1021/acs.bioconjchem.3c00434","title":"Design Parameters for a Mass Cytometry Detectable HaloTag Ligand","year":2023,"lang":"ca","type":"article","venue":"Bioconjugate Chemistry","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital; Institute of Cancer Research; Ontario Institute for Cancer Research; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund","keywords":"Chemistry; Mass cytometry; Alexa Fluor; Flow cytometry; Biophysics; Ligand (biochemistry); DOTA; Polymer; Biochemistry; Molecular biology; Chelation; Fluorescence; Organic chemistry; Receptor","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009738086,0.0009255185,0.0004145716,0.0004122916,0.0003261736,0.0009278565,0.0006950049,0.0008387567,0.00261567],"category_scores_gemma":[0.001230713,0.0004570802,0.000267482,0.0003054701,0.0003296049,0.0005137092,0.000458238,0.0007877286,0.002687069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001330564,"about_ca_system_score_gemma":0.0008981344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004826093,"about_ca_topic_score_gemma":0.0006622145,"domain_scores_codex":[0.9995167,0.00006205891,0.00003876442,0.0001178659,0.0001910373,0.00007362835],"domain_scores_gemma":[0.999355,0.0001515017,0.0001751288,0.00003390685,0.000155767,0.0001286739],"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":[0.0001691528,0.0001012694,0.0004493344,0.0002317305,0.00001145123,0.00005351933,0.00005051572,0.003457178,0.9843038,0.0009679428,0.0004623358,0.009741736],"study_design_scores_gemma":[0.00007974484,0.0006506192,0.0005240817,0.00002083249,0.00002489229,0.0001307341,0.00003896236,0.012236,0.9730356,0.0002765562,0.01294791,0.00003408812],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7309764,0.002620561,0.2471687,0.001285013,0.0002515938,0.001912993,0.001249977,0.002095006,0.01243978],"genre_scores_gemma":[0.8297986,0.001584283,0.1553806,0.0007862974,0.0000864403,0.002673199,0.001097105,0.0002930898,0.008300212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00261567,"threshold_uncertainty_score":0.009653986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03221930785183046,"score_gpt":0.2921452937789509,"score_spread":0.2599259859271204,"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."}}