{"id":"W2624528266","doi":"10.1038/s41598-017-03846-y","title":"Electrophoresis assisted time-of-flow mass spectrometry using hollow nanomechanical resonators","year":2017,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Mechanical and Optical Resonators","field":"Physics and Astronomy","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Indian Institute of Technology Madras; Canada Research Chairs; National Research Foundation of Korea; Canada Excellence Research Chairs, Government of Canada; Department of Science and Technology, Ministry of Science and Technology, India; National Research Foundation; University of Alberta","keywords":"Mass spectrometry; Capillary electrophoresis; Electrophoresis; Analytical Chemistry (journal); Analyte; Resonator; Chemistry; Chromatography; Capillary action; Free-flow electrophoresis; Materials science; Optoelectronics; Polyacrylamide gel electrophoresis; Gel electrophoresis of proteins","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001152649,0.0002267439,0.000441873,0.0001570833,0.0008276991,0.0004401714,0.0004983517,0.0001004334,0.002282638],"category_scores_gemma":[0.0002911804,0.0001914203,0.0003461855,0.0003563701,0.0003082499,0.0001964926,0.0002196082,0.0002356234,0.00006551105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005436701,"about_ca_system_score_gemma":0.0002097213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005722923,"about_ca_topic_score_gemma":0.000001027584,"domain_scores_codex":[0.997099,0.0000565315,0.0006494421,0.0008432102,0.000778857,0.0005729062],"domain_scores_gemma":[0.9971512,0.00006562789,0.0006538227,0.001634178,0.0001756394,0.0003195273],"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":[0.00006617951,0.0004346682,0.02192321,0.00003281759,0.0002064326,0.0003182769,0.00004004807,0.00002271151,0.9402184,0.02031069,0.002148743,0.01427781],"study_design_scores_gemma":[0.0005900534,0.0001624401,0.00584663,0.0001526099,0.0001918067,0.00004466684,0.00005954883,0.01595841,0.6761963,0.2903688,0.009545911,0.0008827585],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9786803,0.00006763022,0.0106042,0.00007562325,0.002605089,0.0002355843,0.00001368571,0.00003822108,0.007679633],"genre_scores_gemma":[0.9800406,7.744803e-7,0.01653852,0.000005442426,0.0001624867,0.00000695074,0.0000198012,0.0000264006,0.003199055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2700581,"threshold_uncertainty_score":0.9986294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01861547038661746,"score_gpt":0.2661507584590589,"score_spread":0.2475352880724415,"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."}}