{"id":"W3202106315","doi":"10.1101/2021.10.07.463410","title":"A sensitive and specific genetically encodable biosensor for potassium ions","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Cancer Institute; Office of Science; National Institutes of Health; Novo Nordisk Fonden; National Institute of General Medical Sciences; Novo Nordisk; National Natural Science Foundation of China; Alberta Innovates - Technology Futures; Univerzita Karlova v Praze; Alberta Innovates; Argonne National Laboratory; U.S. Department of Energy; H. Lundbeck A/S; University of Alberta; University of Saskatchewan; Natural Sciences and Engineering Research Council of Canada; Canadian Light Source; Lundbeckfonden; Canadian Institutes of Health Research; National Science Foundation","keywords":"Biosensor; Potassium; Fluorescence; Electrolyte; Genetically engineered; Ion; Chemistry; Biophysics; Nanotechnology; Biology; Materials science; Biochemistry; Physics; Electrode; Gene; Physical chemistry; Optics","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":[0.0002189179,0.0004076646,0.0002816737,0.0001548767,0.0001406044,0.0003483357,0.0004487671,0.0006848146,0.0004844317],"category_scores_gemma":[0.0002255045,0.00020772,0.0001731314,0.0001811522,0.0003090479,0.0002162395,0.0004617409,0.0007681425,0.0003902633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004134597,"about_ca_system_score_gemma":0.0002650283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004157176,"about_ca_topic_score_gemma":0.0005978873,"domain_scores_codex":[0.9996989,0.00003711865,0.00001411086,0.00006825653,0.0001427289,0.00003891262],"domain_scores_gemma":[0.9999084,0.00001286442,0.00002482935,0.00001355448,0.00001963761,0.00002064657],"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":[0.000006482079,0.000004699932,0.00003947971,0.000006947779,0.000001026154,0.00001074735,0.000002770526,0.00006793923,0.9995024,0.00007838108,0.00002862838,0.0002504342],"study_design_scores_gemma":[0.000005646078,0.00002972337,0.000267688,0.000001074303,0.000002895946,0.00006646571,0.000003152953,0.00109335,0.997098,0.00002714983,0.001400872,0.000004034266],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9467216,0.00103499,0.0476071,0.0004980139,0.0001796942,0.00008019578,0.0008690393,0.0005037039,0.002505735],"genre_scores_gemma":[0.9324705,0.0005747948,0.059559,0.0001448898,0.00002010433,0.00006862942,0.001011421,0.0001590139,0.005991704],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006848146,"threshold_uncertainty_score":0.002999902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01122489223124019,"score_gpt":0.2344585770501496,"score_spread":0.2232336848189094,"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."}}